Nine out of sixteen spleens obtained from cases suspected of immunosuppression by HEV were analyzed. The limited data obtained showed that: (1) field-type HEV circulates in many non-vaccinated western Canadian flocks; (2) field-type HEV circulates in vaccinated flocks with increased recurrent bacterial infections; and (3) the existence of novel point mutations in hexon, ORF1, E3, and specially fib knob domains. This is the first publication showing the circulation of wild-type HEV in HEV-vaccinated flocks in Western Canada, and the usefulness of a novel procedure that allows whole genome sequencing of HEV directly from spleens, without passaging in cell culture or passaging in vivo. Further studies focusing more samples are required to confirm our observations and investigate possible vaccination failure. Hemorrhagic enteritis virus (HEV) is an immunosuppressive adenovirus that causes an acute clinical disease characterized by hemorrhagic gastroenteritis in 4-week-old turkeys and older. Recurrent incidence of secondary infections , may be associated with the presence of field-type HEV in Canadian turkey farms. We speculate that field-type HEV and vaccine/vaccine-like strains can be differentiated through analysis of the viral genomes, hexon genes, and the specific virulence factors (e.g., ORF1, E3, and  Turkey siadenovirus A, a member of the family Adenoviridae, genus Siadenovirus, is a ubiquitous poultry pathogen. HEV has a linear, double-stranded DNA genome of 26.6 kilo base pairs (kb) [Escherichia coli) [Escherichia coli, and processing plant condemnations [Hemorrhagic enteritis virus (HEV) or irs (kb)  and codeirs (kb) ,4,5. HEVia coli) ,8; and  has become low due to vaccination and circulation of avirulent HE in the field , yet, maTransmission of HEV can be horizontal through fecal-oral/cloacal routes ,17,18,19Upon ingestion or cloacal entry, the virus replicates in the gastrointestinal tract leading to a primary viremia from which the virus spreads to other internal organs, such as the bursa of Fabricius and spleen. As HEV is considered a lymphotropic and lymphocytopathic virus ,24, it pHEV seems to have only one serotype, and research in the 70s showed that avirulent strains prevented clinical disease caused by virulent strains . This le2.6 TCID50) between 3.5–6 weeks of age, or twice, using a lower dose  at days 25 and 35. This strategy is designed to reduce field HEV circulation in susceptible birds by immunizing birds with low maternal antibodies with the first vaccine delivery (day 25), and to infect those who were not immunized at the first vaccination due to high levels of neutralizing maternal antibodies or low vaccine intake (day 35). In addition, some farmers rely on circulation and protection generated by field avirulent strains and will, therefore, not vaccinate as there is no manifestation of clinical disease, overlooking the immunosuppressive potential of these field HEV viruses. The Canadian turkey meat industry, with ~160 million kg of turkey meat in 2019 , is smalfib knob domain) [fib knob domain) for determination of HEV origin. Recently, several virulence factors of HEV were identified , E3, and  domain) ,40. HEV  domain) ,41. Our Between July 2017–September 2018, a total of 16 spleen samples from Alberta (AB), British Columbia (BC), and Ontario (ON) were collected from turkey clinical cases submitted to Poultry Health Services (PHS) , a private veterinary practice, by concerned growers with commercial turkey flocks experiencing increased mortality or secondary bacterial infections when compared with industry average, management guides, and/or current literature ,43. The Of the 16 spleen samples, 9 were HEV-positive by qPCR method , which wg for 20 min at 4 °C and the supernatant filtered using a 0.2 µM syringe filter  and kept on ice for further processing. Spleen samples added to sterile tubes prefilled with 1.0 mm zirconium beads  on ice, and homogenized  during three series of 30 s each at 300 RPM. Samples were kept on ice for 3 min in between series. Following disruption, the samples were centrifugated at 7500× A purification method using ultracentrifugation technique with Optiprep as an iodixanol gradient was used to purify and concentrate HEV ,46. Briefib knob gene amplification. Due to the high level of host DNA  in the spleen, low levels of HEV virus in persistently-infected spleens due to HEV seroconversion of the flock at the end of production [Total DNA was extracted from reconstituted vaccine vials, and ultracentrifugation phases using a QIAamp DNA Mini Kit according to manufacturers’ instruction . Invitrogen Platinum SuperFi PCR Master Mix  was used for whole genome amplification, while Platinum Hot Start Taq PCR Master Mix (2×)  was used for ORF1, E3, and oduction , and mulThe entire HEV genome was amplified using the primers: THEV-Whole-F1, and THEV-Whole-R1  targetinSamples which rendered an incomplete whole genome sequencing were subjected to Sanger Sequencing of the ORF1, E3, and Fib genes. The ORF1 gene (1508 bp out of 1553 bp) was amplified using 1 set of primers  resulting in a 1508 bp amplicon. An additional primer was used for sequencing (HEV3’For-951) . The reaThe PCR fragments were cleaned with E.Z.N.A. Gel Extraction Kit  and Sanger sequenced using primers depicted in fib knob domain nucleotide and amino acid alignments were performed using Clustal Omega v1.2.2., and phylogenetic trees were generated using RAxML applying the protein model BLOSUM62+gamma. All the sequences were deposited in GenBank  and NetOGlyc (http://www.cbs.dtu.dk/services/NetOGlyc/) online prediction services . Structural locations of amino acid mutations on 3-D structure of published fowl adenovius-1 (FAdV-1) hexon protein  (GenBank accession #AY849321.1) ,41 under GenBank . Fib knoode 2INY ), human ode 2INY ,55), andFib domain), and ORF7  of which 11 were silent. Two non-synonymous mutations consisted of a ntA231C (aaE77D) on 18-0665, and a ntG2598C (aaE866D) mutation in H.E. Vac, Oralvax HE and vaccine-like sequences 18-0943-AB-2018 and 18-1234-AB-2018  were seqThere is no 3D crystalized molecular structure for HEV hexon protein on which test or analyze the location of these mutations. Although amino acid identities between HAdV-2, HAdV-5, and FAdV-1 range between 47.8–51.36% identity, the overall structure is similar between these viruses consisting on trimers of protein II distributed as three separate “towers” . The locn = 39) were detected, of which 17 were synonymous and 22 were non-synonymous , of which five were non-synonymous. Some point mutations were common to many sequences, such as ntC497A (aaP166H), which included most US isolates from Virginia, and ntA517C (aaT173P), which included some vaccine and vaccine-like sequences . The phyfib knob domain, and similarly to previous research, none of them was silent [fib knob domain on which to analyze the location of these mutations. The amino acid sequences analyzed shared an identity of 97.58–100%. All these mutations can be found in the most exterior part of the domain; three of them were shown to be part of linear loops on the exposed surface of the domain (ntC214A (aaR72S); ntG252T (aaL84F); ntG401A (aaG134D); and the last one, ntG414T (aaM138I), was found to be part of a beta sheet that is also exposed  the first (Cluster 1) considering vaccine and vaccine-like strains (99.82–99.96% nt similarity), and (2) Cluster 2 (99.71–99.98%), including virulent and suspected-virulent strains together with the splenic vaccine, which is not commercially available in Canada. Similarly, as with previous publications, all major ORFs were located as expected . As in pfib knob domain) [Siadenovirus, it seems to resemble the E1A protein of Mastadenoviruses and may code for a transcriptional regulator, this based on the cysteine-rich regions resembling the zinc-binding CR3 domain present in E1A from Mastadenovirus [Recently, several virulence factors of HEV have been identified  . Althoug domain) . These p domain) ,62 and v domain) ,64; and  domain) ,66. Althenovirus ,65. The enovirus ,55,57,58fib knob is implicated in the attachment to the host receptor and it is the only adenoviral protein that is glycosylated [Fib knob domain structures of avirulent (splenic vaccine—GenBank AY849321), and virulent virus (Virulent-IL-1998—AF074946). In short, they found that non-synonymous mutations M65I (at the C’C”-loop), and M87T located (C’-strand) were responsible for a difference of 3Å upwards in the C’C”loop, changing the configuration of the protein. In the present work, we found changes on the same area , as well as others that also may cause further change in the 3-D configuration of the protein, however, further crystallography studies would have to be conducted . The existence of HEV variants in vaccinated flocks with subclinical infections has also been shown . In agreFollowing analysis of previously published virulence factors ORF1, E3, and Fib knob  as well Fib, interestingly, in Canadian field-HEV sequences, these amino acid changes were found in close proximity with other amino acid changes also detected in virulent sequences from Israel and US, suggesting that these mutations are located in functional important locations, perhaps areas targeted by the host immune system. Given that HEV neutralizing antibodies are generated against the hexon and fiber knob proteins, any non-synonymous mutation is potentially important as it may interfere with the induction of immunity induced by vaccines and/or increased virulence of wild type HEV strains [fib knob sequences between these strains are identical [Unlike previous research conducted on virulent and avirulent  sequences , in the  strains . However strains ,36. It identical ,37,71. Ldentical , but alsdentical .−7 to 9.8 × 10−8 substitutions per nucleotide per cell infection) [fib knob domain [The potential efficacy of a given vaccine is determined by the antigenic similarity of the viruses (vaccine and wild type) involved and the neutralization titer generated by the vaccine towards the wild type virus. In general, double-stranded DNA viruses, such as HEV, have the lowest viral mutation rate (ranging between 2 × 10fection) ,73. HEV fection) , and maib domain ,41. The b domain ,8,12. Bab domain ,41, it cb domain ,41.Although the current study yielded valuable data, our samples did not represent the whole meat turkey industry in Canada. We also do not know whether HEV could be recovered from apparently healthy turkey flocks since our focus was to isolate and characterize HEV from clinical samples. fib knob domain gene). Finally, as this works shows the circulation of field viruses in vaccinated flocks, and the failure to recover such sequences from clinical samples obtained from vaccinated flocks, a revision/audit of current vaccination practices by the poultry industry is recommended. The analysis of the HEV sequences have revealed the circulation of field type HEV strains in Canadian turkey flocks with a history of vaccination as well as no vaccination. These strains may be responsible for seroconversion, instead of low-virulent tissue-culture-origin strains. Results suggest that HEVs variability in the field may not be as low as previously thought, as some sequences suggest that some adaptive changes, perhaps caused by an increased vaccine pressure, have occurred and may induce immune evasion (BC strains—


Detecting the genetic and physiological variations in two Japanese quail strains could be used to suggest a new avian model for future breeding studies. Consequently, two estimations were performed on two Japanese quail strains: gray quail strain (GJQS) and white jumbo quail strain (WJQS). The first estimation was conducted on carcass characteristics, breast muscles, breast concentration of collagen type I, and body measurements. In contrast, blood samples were collected for the second estimation for genomic DNA extraction and genetic analysis.A total of 62 alleles out of 97 specific alleles (63.92%) were detected overall loci (14 microsatellite loci) for the two strains. A total of 27 specific alleles of WJQS were observed, and 35 were obtained for GJQS. The percentage of similarity was 48.09% ranged from 4.35 with UBC001 to 100% with GUJ0051. WJQS had greater body weights and a higher value of pectoral muscle and supracoracoideus muscle than GJQS. The breast muscles of GJQS exhibited a higher concentration of type I collagen than the WJQS. Furthermore, males showed higher concentrations of collagen type I than females. WJQS showed a higher body length, chest girth, chest length, thigh length, thigh girth, drumstick length, and drumstick girth (cm) than GJQS. WJQS showed more significant differences in carcass traits compared with GJQS.The physiological differences between WJQS and GJQS were ascertained with microsatellite markers, which indicated high polymorphism between these strains. These observations provided a scientific basis for evaluating and utilizing the genetic resources of WJQS and GJQS in a future genetic improvement program. Coturnix coturnix japonica) is currently the smallest poultry species reared primarily for meat and egg production [Japanese quail , at 5 weeks old, were maintained at the quail experimental farm of the Biological Application Department, Nuclear Research Center, Egypt. Birds were reared in battery cages of 100 × 60 × 50 cm (length × width × height) in size, categorized by each strain, and fed a diet matching with the National Research Council [Two strains of Japanese quails  produced by CUSABIO TECHNOLOGY LLC (http://www.cusabio.com), Houston, TX 77054, USA.Bird weights and biometric body measurements (cm) were collected individually for each strain using a flexible measuring tape. The biometric body measurements (cm) include body length, chest length, chest girth, thigh length, thigh girth, drumstick length, and drumstick girth. Birds were slaughtered, and the empty carcass, liver, heart, intestine, gizzard, proventriculus, and spleen were weighed, recorded, and expressed as a percentage of live body weight. Dressing percentage and carcass yield were estimated as described by Abd El-Moneim et al.  and Abden = 20) and WJQS (n = 22), for genomic DNA extraction according to methods described by Sambrook et al. [Blood samples were collected from GJQS . The premix also contained a vivid green dye, which is separated into blue and yellow dye fronts. The PCR reactions were carried out under the following conditions: an initial denaturation step (for 4 min at 95 °C), followed by 35 cycles of denaturation (for 1 min at 95 °C), annealing (at 48–64 °C for 1 min) at optimized primer annealing temperature  weights compared with GJQS. The relative weight of carcass yield, dressing, liver, heart, proventriculus, and spleen except intestine and gizzard were significantly higher in WJQS than GJQS. Moreover, sex differences were observed inside strain itself, whereas male quail showed significant values in dressing, heart, and carcass yield percentages, while female quail showed significant values in marketing body weight, liver, intestine, proventriculus, and spleen percentages.Variations between two Japanese quail strains in marketing body weight and carcass characteristics are recorded in Table P 0.004), left PC , right supracoracoideus muscle (SC) , and left SC  than the GJQS. Furthermore, sex differences were observed inside strain; females of WJQS showed a higher value of SC and PC muscles than males, while males of GJQS showed a higher value of SC and PC muscles than females.The investigation of the breast muscle characteristics and collagen content of breast muscle in two Japanese quail strains (white vs. gray) is illustrated in Table Microsatellite loci, annealing temperatures, primer sequence, gene bank accession numbers, repeat array, and band size are shown in Table The total number of alleles was 97 out of fourteen microsatellite markers ranged from 3 with GUJ0013 and GUJ0051 to 23 with UBC001 in WJQS and GJQS. The total number of alleles per strain was 62 ranged from one in GUJ0048 to 12 in UBC001 with a mean of 4.43 in WJQS while, the total number of alleles was 70 ranged from two in GUJ0028, GUJ0053, and GUJ0054 to 12 in UBC001 with a mean of 5.00 in Japanese quails strain as shown in Table Specific alleles for the WJQS strain could not be detected using the markers GUJ0013, GUJ0021, GUJ0048, GUJ0051, GUJ0087, UBC002, and UBC005. Also, GUJ0051, GUJ0053, and GUJ0099 produced no specific alleles for Japanese strain, as shown in Table The estimated proportions of WJQS for each individual are represented by the green bar’s length, as shown in Fig. Allelic frequencies were calculated based on all fourteen microsatellite loci. The highest allele frequency overall loci were 1.00 for allele 80 at GUJ0048 locus in WJQS, while the lowest one (0.023) was for allele 65 at GUJ0051 locus in WJQS. Also, the highest average of allele frequency estimated was 0.33 at loci GUJ0013 and GUJ0053. Meanwhile, the lowest one was 0.04 at locus UBC001.Polymorphic information content (PIC) refers to the possibility that a progeny acquires some allelic markers from its father or mother, describing the variation degree of microsatellite loci. The value of PIC for WJQS ranged from 0.19 to 0.89 in GUJ0053 and UBC001, with a mean of 0.58 in WJQS. While it ranged from 0.32 to 0.89 in GUJ0053 and UBC001 with a mean of 0.62 in GJQS as shown in Table In this study, three markers GUJ0013 0.47), GUJ0051 (0.49), and GUJ0053 (0.19) were reasonably informative (0.50 > PIC>0.25). Marker of GUJ0048 (0.00) was a slightly informative marker, and most of the loci were highly informative with WJQS. Four markers GUJ0021 (0.43), GUJ0028 (0.42), GUJ0051 (0.47), and GUJ0053 (0.32) were reasonably informative (0.50 > PIC>0.25), while the majority of the loci were highly informative (PIC ≥ 0.50) with GJQS. The analysis of molecular variance estimated by the Arlequin 3.5 software package as standard genetic strain input data is presented in Table , GUJ0051The significant differences in the two-color variants studied (WJQS and GJQS) in the marketing body weight and different body measurements such as body length, chest girth, chest length, thigh length, thigh girth, drumstick length, and drumstick girth reflect the differences between WJQS and GJQS in body sizes and shape, indicating positive relationships between body weights and body measurements Tables  and 6. MP < 0.001), respectively (Table P < 0.001), respectively. It is well-known that intramuscular collagen is an essential parameter to the meat industry; an increased amount of this component may affect toughness and meat quality. In other words, the most abundant fibrous form of collagen in muscle is type I, which considers the main structural protein of connective tissues present in meat, providing meat toughness and rigidity and involved in the structural integrity and several physiological functions [Furthermore, it is generally accepted that both PC and SC muscles are positively correlated with marketing body weight, muscle mass, and meat quality. In this mention, Młynek et al.  showed tly Table . Furtherunctions , 35. Morunctions . TherefoExamining the results of the 14 microsatellite markers in this work showed some genetic differences in two quail strains WJQS and GJQS. As a result, the observed genetic differences confirmed the presence of physiological variations between WJQS and GJQS, such as body weight, carcass characteristics, body measurements, breast muscle weights, and collagen type I concentration of breast muscle. Our results are consistent with similar studies conducted by Charati et al.  and MoraThis study showed highly physiological differences between WJQS and GJQS in live body weight, carcass characteristics, body measurements, breast muscle weights, and collagen type I concentration of breast muscle. These physiological variations were ascertained with selected 14 microsatellite markers, which indicated the relatively rich genetic variation of the two strains and a significant genotype of WJQS than GJQS. These results succeeded in introducing a scientific basis for the evaluation and utilization of genetic resources of WJQS and GJQS in the next breeding programs for genetic improvement of the breed in an attempt to stop the continuous inbreeding system in quail farming and, consequently, improve the production performance of Japanese quail.


CDK5 is a serine/threonine type kinase that is mainly found in nerves. It is a target that has been studied primarily in neurological disorders, but recently it has been newly recognised for its importance in cancer. In this review, we mentioned the role of CDK5 in normal cells and the latest findings that CDK5 contributes to ten hallmarks of cancer and cancer-nerve connections. Also, we introduced representative CDK5 inhibitors and suggested the possibility of CDK5 inhibitors as treatments for refractory cancer.Cyclin-dependent kinase 5 (CDK5), which belongs to the protein kinase family, regulates neuronal function but is also associated with cancer development and has been proposed as a target for cancer treatment. Indeed, CDK5 has roles in cell proliferation, apoptosis, angiogenesis, inflammation, and immune response. Aberrant CDK5 activation triggers tumour progression in numerous types of cancer. In this review, we summarise the role of CDK5 in cancer and neurons and CDK5 inhibitors. We expect that our review helps researchers to develop CDK5 inhibitors as treatments for refractory cancer. Cyclin-dependent kinase 5 (CDK5), a proline-directed serine/threonine kinase, is known as a modulator of neuron function, including neurite outgrowth, neuron migration, and neuron degeneration ,3,4,5,6.CDK5 was first identified by Hellmich in 1992 as neuronal cell division control 2-like kinase due to its high sequence homology of the cell division cycle protein 2 (cdc2) . It has Unlike other CDK family members that require cyclin for activation , CDK5 map35, a membrane–docked protein, consists of two parts: an N-terminal region containing a p10 component and a C-terminal region containing p25 . The p108 and Thr138 .,24.19,24 calpain ,44,45. C calpain ,44. This calpain ,47.The presence of p10 helps to localise CDK5/p35 mainly in the perinuclear and plasma membrane regions and less prominently in the nucleus-the cleavage of p10 from p35 by calpain yields p25. Thus, CDK5/p25 complexes are enriched in the cytosolic region and nucleus ,24. Howep39 is an isoform of p35 and an activator of CDK5; it also has the same position as p35  41,48].,48.41,488, leading to localisation in the cytoplasm . Mo. Mo26]. Evidence indicates that cyclin D1 fails to stimulate CDK5 activity . AbnormaCyclin E is expressed in neuron and forms complex with CDK5  30]. Li. Li30]. Glutathione-S-transferase P (GSTP1) inhibits the activity of CDK5 by dislodging p25 and p35 from CDK5/p25 and CDK5/p35 complexes, respectively  22]. Ev. Ev22]. Munc 18 (p67) is part of a multimeric (supramolecular) complex containing Cdk5/p35 and regulates CDK5 activity  51,52].,52.51,5215 to enhance the activity of CDK5 ..217].50 = 7 μM), CDK2 (IC50 = 7 μM) and CDK5 (IC50 = 3 μM)   [218]. OR)-roscovitine, seliciclib] is a small molecule that inhibits cyclin-dependent kinase (CDK) through direct competition with ATP at the ATP binding site . I. I50 = 0Dinaciclib (SCH 727965) is a small molecule multi-CDK inhibitor targeting CDK 2/5/9 with an improved therapeutic index in comparison with flavopiridol  223]. T. T223]. 50 = 0.21 μM), CDK2 (IC50 = 0.047 μM), CDK4 (IC50 = 0.1 μM), CDK5 (IC50 = 0.13 μM), CDK6 (IC50 = 0.17 μM), and CDK9 (IC50 = 0.13 μM)  ; Table 4Like AT7519, 20-223 (CP668863) is a CDK inhibitor derived based on the 4-aminopyrazole core  225,242242. 20-250 = 4–70 nM) and CDK5 (IC50 = 75 nM)  ; Table 4Recently, TFP5/TP5, a peptide derived from p35, was found to inhibit the hyperactivity of CDK5/p25 complex without influencing endogenous CDK5/p35 complex ,248,249.Although there are various types of CDK5 inhibitors and researches are ongoing to develop selective CDK5 inhibitors , specifiWe have presented a summary of CDK5 as a biomarker and a new target in cancer treatment. CDK5 is overexpressed in various cancer, and this upregulation has been proposed to facilitate tumour proliferation and metastasis. There is much research regarding the effect of CDK5 on cancer hallmarks. However, the effects of CDK5 on some hallmarks have not yet been studied.Notably, CDK5 is involved in the metabolic processes associated with glucose consumption and facilitating cell proliferation. Glucose is known as an essential nutrient for cancer development. This raises the question of whether CDK5 manipulates tumour development through glucose uptake. This novel role of CDK5 needs to be studied further.CDK5 was first known as a kinase regulating neuronal function. Recently, evidence has shown the involvement of CDK5 in cancer. Therefore, among the several findings that have been studied in neurons, for example, the roles of CDK5 related to the reorganisation of cytoskeletons, including microtubules, are likely to apply to cancer research. CDK/p35 is activated in several cancers and promotes proliferation and migration of cancer cells. However, other groups reported that CDK5 inhibits proliferation and migration of cancer cells. Recently, Sharma et al. have utilised the melanoma cells expressing analogue-sensitive CDK5, which made it possible to specifically inhibit CDK5 in cancer cells, clearly demonstrating that inhibition of CDK5 in melanoma cells inhibits the metastatic spread of melanoma .If the researchers’ approach can be applied to various carcinomas involving CDK5, clear conclusions can likely be drawn from the conflicting results associated with CDK5 in different cancers. If it becomes clear that CDK5 promotes cancer development and progression, the development of CDK5 specific inhibitor is expected to accelerate further. Since the research results on inhibitors of CDK5 have been conducted to develop therapeutics for neurological diseases, if these results can be used to develop therapeutics for various cancers, it is expected to create a specific inhibitor for CDK5 at a relatively rapid pace. Besides, since CDK5 is a target present in nerves, the neurological side effects of concern can be minimised through a strategy that prevents the passage of the blood-brain barrier, and a study of CDK5 therapy in carcinomas where nerves are involved in the growth and progression of cancer. In conclusion, CDK5 is a fascinating target in cancer. We look forward to the day that the development of CDK5 specific inhibitors through many studies will be successful, and it will become a therapeutic agent for various refractory cancers.


M 6.0 South Napa, California, earthquake rupture, each dominated by either co- or post-seismic shallow fault slip. We combine mobile laser scanning (MLS), active-source seismic tomography, and finite element modeling to investigate how deformation rate and mechanical properties of the shallow crust affect fault behavior. Despite four orders-of-magnitude difference in the rupture velocities, MLS-derived shear strain fields are remarkably similar at the two sites and suggest deceleration of the co-seismic rupture near Earth’s surface. Constrained by the MLS and seismic data, finite element models indicate shallow faulting is more sensitive to lithologic layering and plastic yielding than to the presence of fault compliant zones . Although both elastic and elastoplastic models can reproduce the observed surface displacement fields within the uncertainty of MLS data, elastoplastic models likely provide the most reliable representations of subsurface fault behavior, as they produce geologically reasonable stress states and are consistent with field, geodetic, and seismological observations.Poor knowledge of how faults slip and distribute deformation in the shallow crust hinders efforts to mitigate hazards where faults increasingly intersect with the expanding global population at Earth’s surface. Here we analyze two study sites along the 2014  M 7.9 San Francisco earthquake produced what remains one of the most rigorous characterizations of fault rupture at Earth’s surface, including detailed records of off-fault plastic deformation1 and inferred shallow slip gradients2, phenomena that continue to puzzle earth scientists today. Since these pioneering studies, process-based knowledge of surface rupture and shallow deformation has remained elusive, due largely to the paucity of spatially coherent geodetic data close to active faults. This data gap is further compounded by the poorly understood mechanical behavior of the shallowest portion of Earth’s crust, where deeper, competent bedrock typically transitions into poorly consolidated, chemically-altered units and/or alluvium. For example, attempts to explain the hypothesized “shallow slip deficit,” an apparent discrepancy between fault slip in the shallow (0–3 km) and deeper (>~3 km) crust4, have appealed to both improved data coverage6 and better quantified uncertainty in the constitutive properties of the shallow crust8. Importantly, our lack of knowledge regarding shallow fault behavior impedes our ability to forecast seismic hazard, with significant financial and public safety consequences9. For instance, the Uniform California Earthquake Rupture Forecast10 and U.S. Geological Survey National Seismic Hazard Maps11, which inform insurance rates and emergency plans, depend on measurements of fault slip at Earth’s surface that do not consider possible subsurface variations12. Additionally, the emerging field of Fault Displacement Hazard Analysis, which aims to improve construction practices near faults , relies on empirical relations that neglect variations in the mechanical properties of the host lithology14.Investigators of the 1906 19. Two factors receiving significant attention for their potential to affect fault slip and distributed deformation are compliant zones21 and elastoplasticity24. Compliant zones correspond to densely fractured regions surrounding faults with reduced elastic stiffness25, particularly following earthquakes27, that locally reduce seismic velocities29 and enhance elastic deformation21. Previous studies have argued, however, that distributed deformation around some faults cannot be fully accounted for by elastic strain within compliant zones31. Such deformation may arise from mechanisms of plastic yielding, for which evidence exists in paleoseismic trenches33. Although gravitational effects in layered media, including the acceleration of viscoelastic relaxation at long wavelengths and attenuation of the overall vertical displacement field, become important at length scales greater than several elastic plate thicknesses and/or over time periods much greater than the relaxation time, the effect on strains is negligible in the near-field and within a single earthquake cycle38.Advances in near-field geodetic techniques allow us to accurately quantify displacement fields near faults with unprecedented spatial resolution, often revealing distributed (or “off-fault”) deformation that is more complex than originally assumed40 and deformation rate 42. Without greater confidence in how these proposed factors affect faulting near Earth’s surface, we cannot reliably use the results of near-field geodetic analyses to infer shallow deformation, nor can we formulate models to predict fault slip and deformation in future events.Relatively unstudied factors that may affect near-field deformation include layered elastic propertiesM 6.0 South Napa, California, earthquake rupture (2014-08-24 10:20:44 UTC) nucleated at a depth of 9.4 km and propagated unilaterally updip along the West Napa Fault Zone (WNFZ), approximately following the base of a northward-shallowing alluvial basin47  were observed on the eastern subsidiary fault strands43. We focus on the westernmost strand, which produced the majority of co-seismic and all post-seismic surface deformation50. On this principal strand, co-seismic surface deformation was largely confined to the north where the shallow rupture passed through sedimentary bedrock of the Great Valley Group51. Within the basin to the south, surface deformation primarily accrued post-seismically, eventually matching the northern co-seismic surface offsets  clay-rich shear zone at a depth of 9 m53, indicating the primary rupture terminated between ~3–9 m depth at that location. Our conclusion that the rupture remained buried does not preclude the occurrence of distributed deformation off the principal fault surface. In fact, preliminary analysis of the continuous drill core reveals off-fault subsidiary structures with individual offsets <1 cm53. Thus, the South Napa earthquake rupture occurred on a pre-existing fault plane, but did not breach Earth’s surface co- or post-seismically.Hundreds of fault-crossing grape vines recorded surface deformation due to the South Napa earthquake in high-resolution. A deformed “vine row” typically displays continuous right-lateral deflection across a 5 to 30 m wide zone containing a narrower array of left-stepping, echelon, mixed-mode fractures46, suggesting an average hypocenter-to-site rupture velocity of 2.7 km/s. Landowners first surveyed the site ~4 hours post-earthquake, finding two fault-crossing PVC pipes had broken54. The first scientific measurement, made 35 hours post-earthquake, recorded a single vine row offset 40–45 cm51. Subsequent lidar surveys of 80 vine rows, made 9 and 37 days post-earthquake, found average offsets to be 45 ± 8 cm and 44 ± 8 cm, respectively, suggesting that any post-seismic deformation was not significant12. In contrast, surface deformation at Saintsbury was predominantly post-seismic. A fault-crossing road ~500 m northwest of Saintsbury was undeformed ~3 hours post-earthquake, where surveyors found a 10 cm high scarp the following day51. Kinematic finite fault models show the top of the co-seismic rupture at approximately 2 km47 to 2.5 km46 depth at Saintsbury. Taking 3 hours as the minimum time for slip to reach the near-surface, the estimated post-seismic rupture velocity from the co-seismic slip patch to the surface was 1.9 × 10−4 to 2.3 × 10−4 km/s, four orders-of-magnitude slower than at Buhman. Alignment arrays, repeat laser scans, and radar interferometry all indicate substantial afterslip near Saintsbury, producing 40–50 cm total surface offset 55.We target two sites along the principal fault rupture, Buhman Fig.  and Sain12, which we smooth using non-parametric Gaussian kernel regression in order to calculate shear strain   to image vineyard deformation within ±~50 m of the fault. The MLS point cloud for a typical vine row includes >50,000 laser returns, each referenced in three dimensions at approximately centimeter-scale resolution and accuracy56) Fig. , suggest61. Details on seismic data acquisition and processing to constrain elastic moduli are presented in the Methods section. We calculate elastic moduli assuming uniform density and isotropic linear elasticity. The assumption of uniform density is the primary source of uncertainty in the elastic moduli, which we discuss in Supplementary Note We use high-resolution (1 m source/receiver spacing) active-source seismic surveys to infer the subsurface seismic velocity structure and corresponding distribution of elastic properties at the Buhman and Saintsbury sitesG) and Young’s (E) moduli vary significantly with depth, with a soft layer  running sub-parallel to the surface topography, and a stiff layer  forming an asymmetric step at depth  varies from ~0.4–0.49  for material surrounding the fault within +30/−40 m horizontal distance. Because ν = 0.5 defines an incompressible elastic material, we interpret that this near-fault zone is fluid-saturated64. Elevated Poisson’s ratio also is consistent with damage  surrounding the fault65.At Buhman, the seismic data indicate that the shear  in the center grading outward to stiffer material , agrees with previous characterizations of fault compliant zones61. Relative to maximum G in this survey, the compliant zone representing a 50% decrease in rigidity is ~50 m wide. As at Buhman, the ν = 0.44 contour occurs at ~5 m depth below the rupture trace and a highly incompressible region (ν > 0.48) surrounds the fault within +20/−30 m horizontal distance.At Saintsbury, the seismic data suggest ace Fig. , in cont28, since surveys covering the greater Napa region found a >400 m wide compliant zone with a 35–50% relative velocity reduction, and a more prevalent ~200 m wide low-velocity zone at shallow depths67, providing an even poorer match to the MLS data.Comparing the seismic tomography models with the MLS data Fig.  reveals Mechanical models allow us to test systematically how variations in mechanical properties affect fault behavior. We do this using 3D quasi-static finite element models and the range of mechanical properties inferred using seismic tomography for the Buhman and Saintsbury study sites Fig. . Details12. Our analysis focuses on near-field deformation within ±50 m of the fault, which is not significantly affected by variable fault slip below 50 m depth , geodetic  for plastic yielding during the South Napa event, we define the continuum constitutive behavior as either linear elastic or Mohr-Coulomb elastoplastic. Frictional plastic yield criteria, including Mohr-Coulomb and Drucker-Prager formulations, were originally developed to simulate the failure of granular materials69, and commonly are used to model fault-driven deformation in the shallow crust70 . Elastic properties are based on the seismic tomography models  free surface  depth often focuses within zones <1 cm wide, though fault structure often “flowers” upward toward Earth’s surface where the observed deformation may be distributed across a zone that is tens-of-meters wide88. Additionally, boreholes crossing actively creeping strike-slip faults record concentrated deformation within zones narrower than 3 m wide, even within alluvium and at <25 m depth90. Furthermore, deformation of subsurface infrastructure, including tunnels91 and qanats (aqueducts)79, during historic earthquakes indicates localized fault slip within tens-of-centimeters at shallow depth (~30 m), even where deformation was distributed across tens- to hundreds-of-meters at Earth’s surface.Our models assume that the distributed deformation observed at Earth’s surface during the South Napa event resulted from slip on a buried rupture, defined as a narrow structure across which the majority of shear displacement localizes. This inference is supported by geological studies of exhumed fault structures, which typically indicate that the majority of displacement occurs within a highly localized zone79 to as narrow as <50 microns at 7 km depth93. Near Earth’s surface, continuum deformation governed by frictional plastic yielding  should progressively narrow with depth as mean normal stress increases22. Thus, we expect that the width of the deformation zone observed along the South Napa rupture should taper downward toward a much narrower zone of localized shearing. At the Saintsbury site, the observation of a 2–3 cm wide principal slip zone in drill core collected at 9 m depth supports this hypothesis53. It is not possible from the core to determine how much offset accrued across the localized clay-rich shear zone. Based on empirical displacement-thickness (D-T) scaling relations (linear with D/T ranging from 10 to 100 for brittle faults94), we infer that this 2–3 cm thick zone accrued significantly more displacement than the subsidiary shears, which typically have thickness on the order of a millimeter or smaller53. Although we cannot absolutely eliminate the possibility that the deformation zone extends downward with constant width , this would be inconsistent with the mechanical theory and previous geological observations outlined above.In addition to geological observations, theoretical mechanics suggests that deformation should occur within a narrow zone at depth. At seismogenic depths where earthquake ruptures nucleate and propagate, thermally-driven dynamic weakening mechanisms require slip to localize within several centimeters28. Importantly, these previous studies evaluated triggered deformation within a compliant zone due to slip on a fault located >10 km away, whereas our study considers deformation due to slip on a fault located within the targeted compliant zone.Our multi-disciplinary approach reveals several important sensitivities of shallow fault slip and near-field deformation. Mechanical models Fig.  demonstr95 and systematic differences between near- and far-field displacements56, indicating a slip reduction within the shallowest tens to hundreds of meters of Earth’s crust.In contrast to compliant zones, we find that horizontally layered elastic stiffness representative of lithologic layering can significantly affect shallow fault behavior. Compared to a homogeneous elastic model, those including a soft surface unit overlying a stiff basement unit Fig. , the sti97, and with mechanical modeling of faults in Von Mises elastoplastic73 and non-linear viscous98 media. Whereas the elastic models produce slip gradients that would require stress near the fault tip to exceed the expected yield strength for near-surface materials, the elastoplastic models inherently limit the stress state to geologically appropriate values regulated by the Mohr-Coulomb yield criterion. Additionally, the elastoplastic models are consistent with independent evidence for plastic deformation during the South Napa event . Although we cannot use seismic data to constrain plastic properties, future work may allow us to infer qualitative variations in yield strength based on observations of plastic deformation features  and knowledge of whether the material is strain-hardening or -softening from mechanical testing of core samples.Compared to the layered elastic models, elastoplastic models produce even greater shallow fault slip and more abrupt slip reduction at the buried fault tip Fig. . This reFinally, our study encounters the long-recognized challenge of non-uniqueness inherent to all geodetic studies: surface displacement fields can be fit equally well by either elastic or elastoplastic models with different input parameters Fig. . The corWhere land access is not permitted, geodetic studies would benefit from additional knowledge of mechanical properties for a variety of geologic settings. Because geologic maps exist for most continental regions, particularly where active faults are recognized, constraining a site’s surface geology is nearly always possible. Then, a geodetically-constrained model can implement mechanical properties appropriate for that setting based on site-specific data acquisition and analysis possible at another locale with similar surface geology.101. MLS point clouds for each vine row have significant scatter due to the presence of branches and leaves  at ±15 m from the mapped fault trace. We average the slopes for the two limbs, and assume the undeformed  vine row followed this average trend through the fault zone. We then calculate shear strain in 1 m increments as: her Fig.  by settiher Fig. .At each study site, we conduct active-source seismic surveys along a ~120 m long transect approximately perpendicular to the fault trend Fig. . The surWe locate geophones to better than ~1 cm accuracy in a global reference frame by surveying each station with dual frequency GPS equipment. For each line, a continuously operating base station is operated within 50 meters of the seismic stations. Each geophone location is surveyed by a rover GPS unit for more than a minute at 1 Hz sampling frequency. The ensemble of the base station and rovers are processed using kinematic carrier phase processing software (GrafNav) and placed in a global reference frame using a nearby continuous GPS base station.104. Because geophone and shot locations are collocated with 1 m spacing, and due to the redundancy of having a shotpoint at every geophone, we parameterize the P- and S-wave velocity models using 1 m horizontal (x) and vertical (z) intervals. For the tomographic inversions, we use 1D starting models developed from shot-gather modeling. Significant smoothing in both x- and z-directions is used for initial inversion iterations, with the amount of smoothing slowly decreasing with iteration number. We expect high (<5 m) spatial resolution at both sites, given the high spatial density (1 m spacing) of the sources and receivers, which resulted in >10,000 first break arrival picks to invert each model (both P- and S-wave)105.We generate seismic tomography models based on first arrival travel times and a previously published modeling codep) and S-wave velocities (Vs) inferred from the tomography model assuming uniform density, ρ = 2000 kg/m3 71, and an isotropic linear elastic solid with the following equations: G = ρVs2; ν = [Vp2 − 2Vs2]/[2 (Vp2 − Vs2)]; E = 2G (1 + ν)106.Elastic moduli Fig.  are dete107 with the Standard implicit solver accounting for geometric nonlinearity. To reduce computation time, an iterative solver based on the Krylov method108 is used with the default convergence tolerance . All models presented here converged without error.Finite element models are constructed and analyzed using Abaqus FEA109. Previous studies have shown near-surface granular materials to follow frictional plastic yield criteria, including Mohr-Coulomb, with non-associated flow69. We use the Mohr-Coulomb, rather than Drucker-Prager, yield criterion in order to minimize assumptions  and approximations that are otherwise required to match laboratory-constrained parameters  to the Drucker-Prager model, particularly when the angle of internal friction exceeds 22°107. All models assume homogeneous density ρ = 2000 kg/m3 and fault friction µ = 0.4.The 3D model domain  Gravitational loading to instate a lithostatic pressure gradient. The gravitational load is in equilibrium with an initial geostatic stress field defined for the model domain. By the end of the first step, the gravitational load generates <2E-5 m vertical displacement and <4 Pa Mises equivalent stress across the model, along with the desired lithostatic pressure gradient, which increases linearly from 0 MPa at the modeled Earth’s surface to 19.6 MPa at the base of the model; (2) Prescribed uniform right-lateral fault slip of 0.5 m below 50 m depth. Because the MLS data do not consistently capture surface deformation beyond ±50 m from the fault, our comparison between model results and MLS data is restricted to that very near-field region. Our models assume uniform slip below 50 m, though fault slip during the South Napa earthquake likely was more complicated. We evaluate our assumption of uniform driving slip using a series of model tests  dislocation solution40 for slip on a vertical planar fault embedded in a layered elastic medium  a vertical array from the surface to 50 m depth at the center of the fault, from  =  to . Surface displacements  a transect at the modeled Earth’s surface orthogonal to the fault and across the entire model domain, from [ts Figs. , 4a,b ants Figs. , 4c,d weSupplementary Information.


The letter of recommendation is currently an integral part of applicant selection for residency programs. Internal medicine residents will spend much time and expense completing sub-specialty away electives to obtain a letter of recommendation. The purpose of this study was 1) to examine a large sample of reference letters in order to define essential components of a high-quality letter, and 2) to elucidate the relationship between quality of reference letter and the letter writer.We conducted a two-phase study. In phase one, a large sample of letters of recommendation was examined using an audit tool as a coding framework. A 5-point composite endpoint of high-quality letter components was subsequently developed. In phase two, program director letters were compared to non-program director home institution and non-home institution elective letters based on inclusion of components of the 5-point composite endpoint using Chi square testing.p < 0.001). A significantly higher proportion of program director letters had 4–5 high-quality components (62.5%) compared to 2% of non-program director home institution letters and 0% of elective letters (p < 0.0001).715 letters were examined . High-quality letter components were: nature of relationship, duration of relationship, In Training Evaluation Report information, research involvement and comments on areas for improvement. Program director letters had a significantly higher proportion (10.4%) of all 5 high-quality components, compared to 0% in both non-program director home institution letters and elective letters (Letters of recommendation from elective rotations are of the poorest quality and such rotations should not be pursued for the sole purpose of obtaining a letter. The low quality of elective letters leads to the recommendation that writers should decline to write them, programs should not require them and trainees should not request them. Program directors write the highest quality letters and should be a resource for faculty development. Clinical supervisors can use the 5-point composite endpoint as a guide when writing letters for applicants. The Letter of Recommendation (LOR) is an integral part of applicant selection for internal medicine subspecialty training programs. LORs are considered one of the most important factors in ranking candidates to postgraduate subspecialty programs and may be helpful in predicting residency retention rates –5. HowevLORs have been found to lack a meaningful comparison of the applicant to peers and often fail to include concrete examples demonstrating applicant performance . LORs wiOur previous research which included a survey of Canadian internal medicine program directors has provided some insight into the challenges with letter writing and interpretation. Program directors (PDs) felt LORs lacked a common vocabulary and format and that referees often used variable rating scales or similar statements that did not differentiate between candidates. One example of this is the observation that a significant proportion of residents appeared to be in the top 5% of applicants . The CanWe partnered with the Canadian Resident Matching Service (CaRMS) to evaluate LORs for internal medicine residents applying to subspecialty training programs. The study objectives were to: 1a) elicit the key components of letters which affect quality through a large audit of LORs to subspecialty internal medicine programs in Canada between 2011 and 2014 and b) subsequently define the components of a high-quality letter; and 2) compare PD letters to non-PD home institution and non-home institution elective letters (elective letters) based on the inclusion of high-quality components.Ethics approval was obtained from the Queen’s University Health Sciences & Affiliated Teaching Hospitals Research Ethics Board and the Canadian Resident Matching Service (CaRMS) Board.This study was designed in two phases.The objective of phase one was to identify common components present in LORs and then by consensus, select the components that are necessary for a LOR to be deemed high-quality.CaRMS provided 738 de-identified reference letters that had been submitted to subspecialty internal medicine programs  over a 3-year period (2011–2014). Letters had been randomly selected by staff at CARMS and the distribution across specialties correlated well with the overall distribution for the match from 2011 to 2014. An audit tool was established based on a literature review of LORs in an effort to collect quantitative and qualitative data, including information and examples according to categories of CanMeds roles and details of letter writer .The research assistant conducted content analysis , 15 usinA composite endpoint consisting of five items was created to define a high-quality LOR. The composite endpoint was created by selection of the five most valuable components of LORs from the list of identified common components, based on: 1) the opinions of Canadian internal medicine program directors obtained through a survey  Letters from PDs (PD letters) were compared to (i) letters by non-PDs from the home school (non-PD home institution letters), and (ii) letters obtained on elective rotations (elective letters). Letters were compared with respect to the inclusion of individual components of the 5-point composite endpoint. The inclusion of In Training Evaluation Report (ITER) information was identified as one of the components of the composite endpoint. Upon reflection that elective letters were unlikely to include this data, a separate comparison was also performed, removing the ITER component and leaving a 4-point composite endpoint. Analysis was also performed to assess if a writer had met the criteria for a good to high-quality letter by including a majority of the components.Chi square testing was performed to compare frequencies using SPSS Statistics, version 24 . A sample size of 105 per group was necessary to demonstrate a 20% difference in proportion of high-quality letters using three-step pairwise comparison in an ANOVA.nature of relationship between the referee and candidate, such as rotation supervisor, research supervisor, and/or program directorduration of this relationship-measured in weeks.inclusion of In Training Evaluation Report (ITER) informationresearch involvement comments, often outlining role in specific projectsarea for improvement or critique comments.The components necessary for a high-quality letter were determined to be:Given the possibility that only PDs would have ready access to ITER information, we also performed the analysis excluding this component, using a 4-point composite endpoint.738 letters were reviewed, with 715 included in the final analysis. Twenty-three were excluded due to duplicates or redaction beyond ability to extract meaningful information. The distribution of reference letters was: 398 non-PD home institution letters (55.7%), 201 PD letters (28.1%), and 116 elective letters (16.2%). Letters were written for 206 applicants, with a range of 1–5 letters per applicant reviewed. Applicants were applying for 9 specific sub-specialties, with good representation of the breath of sub-specialty internal medicine. There were 113 letters for which the specialty being applied for was not evident. There were no letters of application for allergy, infectious disease, or endocrinology. Letter writers were affiliated with 33 different institutions within Canada and the United States.p < 0.001) , PD letters had a significantly higher proportion of letters that met this target 10.4%), compared to 0% in both non-PD home institution letters and elective letters  Table .Table 1p < 0.0001) (Table p < 0.0001) (Table p < 0.0001)  compared to 2% of non-PD home institution letters, and 0% of elective letters p < 0.000  why would trainees get these letters, and 2) did this study miss some important aspect of the letter that would make letters from electives important? While our data suggest elective letters are not of good quality, and thus seemingly not useful overall, they may be a necessity for a particular institution, regardless of how non-specific the information within them, as suggested by recent papers from the surgery field , 19. TheThe current study does have certain limitations. While exposing key differences in letter quality according to the letter writer, further exploration of this data is somewhat limited. To ensure anonymity, the letters underwent redaction prior to release by CaRMS, with demographic data including age, gender, and candidate home institution name being removed. Moreover, we were unable to correlate these findings with subspecialty match or residency performance results, thus limiting us to examining the process rather than outcomes that may be of interest to a PD. We put a lot of weight on the opinions of internal medicine PDs, largely because of their experience in both writing and reading letters of recommendation. However, there are other members of selection committees, whose views and opinions of a quality letter may differ. In consideration of this, our composite endpoint was developed with input from the internal medicine PD survey, but also with input from a panel of academic internal medicine subspecialists who sit on various residency training selection committees. Lastly, the current study only looked at letters for application to the subspecialty internal medicine match and results may not be transferable to programs accepting medical students into their first year of residency training (PGY-1).LORs from elective rotations: We recommend that letters from elective rotations should not be mandatory for consideration of acceptance into a program, as well as consideration of a faculty wide approach/position that writers will not provide letters based solely on elective rotations. This recommendation would presumably lead to trainees asking for letters from other sources, likely faculty that know them better and thus can provide a higher quality letter.Faculty development: Program directors are a potential resource for faculty development and can provide guidance to letter writers based on their experience and expertise in postgraduate medical education. Institutions should approach program directors for faculty development strategies that will lead to improved quality of LORs.Letter writers: Clinical supervisors who are writing letters for applicants in the Medicine Subspecialty Match can use the components of the 5-point composite endpoint as guide for the inclusion of important components  information, research involvement and comments on areas for improvement). Also, if a supervisor does not feel they can comment on one or more of these components, then it would be acceptable to decline a request for a LOR from an applicant.Letter readers: Similarly, those reviewing applicants’ portfolios can use the components of the 5-point composite endpoint to judge the quality of the letter.Applicants: Applicants should be aware of what program directors value in LORs and should direct their requests to supervisors who are appropriate and capable of commenting on the key components.In conclusion, LORs continue to be variable in quality. There continues to be a quality gap in LORs for subspecialty medicine positions, in particular with respect to letters from elective rotations. Program directors write the highest quality LORs and should be a resource for faculty development. LORs from away rotations are of the poorest quality and such rotations should not be pursued for the sole purpose of obtaining a letter. Future studies are needed to assess outcome and to study clinical performance of trainees who have letters from elective rotations. Future research could involve surveying trainees and program directors for deeper insight into what drives LORs and opportunities for improving them.


Complementary foods based on habitual cereals such as maize have been linked with the promotion of undernutrition in young children. Blending the starchy-rich maize with nutritious-rich indigenous food such as oyster mushroom could improve the nutritional composition of complementary foods. This study investigated the effectiveness and suitability of oyster mushrooms in improving the nutritional value of maize flour commonly used as a bulk ingredient in complementary foods. Flour made of well-cleaned and sun-dried oyster mushroom was blended with maize flour at 0% (control), 30%, 40%, and 50%. Proximate composition, mineral density, and sensory evaluation were determined using standard procedures. Significant improvement in the nutritional quality of formulated flour blends with all proportions of mushroom flour was obtained . Blending maize flour with 30%, 40%, or 50% oyster mushroom flour improved the protein content of formulated flour blends from 8.63% to 18.20%, 8.63% to 20.37% and 8.63% to 22.75%, respectively. The increase in ash and fiber content ranged between 82.52% to 84.16% and 50.69% to 58.35%, respectively. Mineral content of formulated flour blends was improved from 62.89% to 64.72% (iron), 7.63% to 22.69% (zinc), 77.48% to 78.02% , and 67.55% to 67.64% (potassium). Sensory scores of porridges prepared from formulated flour blends showed good acceptance for the colour, flavour, and aroma of the porridges from three formulated flour blends. Overall, this study recommends blending oyster mushroom with maize flour to improve the nutritional content of formulated flour blend for young children who rely on maize porridge as their complementary food. Maize is one of the essential annual cereal crops used as a staple food after rice and wheat worldwide . Maize sWhite maize, predominantly used in Tanzania, is regarded as nutritionally deficient among cereals. They contain low protein levels (9.3%) than their counterparts, such as wheat and sorghum, whose protein content is above 10% . FurtherTo date, Tanzania is among the leading countries in Sub-Saharan Africa with a high rate of undernutrition, occurring in both forms of underweight, wasting, and stunting . Stunting is the major form of undernutrition to young children in Tanzania, accounting for 31.8% of all cases . The drivers of dietary-related noncommunicable diseases (NCDs), including undernutrition, are mainly unhealthy diets for both children and the elderly. Nonetheless, Tanzania is home to a wide variety of indigenous and nonindigenous crops, including pulses, nuts, cereals, fruits, and vegetables, which contain essential nutrients that contribute to healthy and productive lives. Therefore, improving the nutritional value of habitual cereal-based complementary foods such as maize using other existing crops could promote food diversification during the complementary feeding period.Mushrooms are widely reported as ingredients of various complementary foods to promote indigenous foods as a critical contributor to nutritious complementary food. Ikujenlola and Ogunba  studied Pleurotus species, are among the most common types of cultivated mushrooms in the world [Oyster mushrooms, commonly known as he world . This tyhe world . Oyster he world . Additiohe world . Studieshe world .Pleurotus ostreatus) in improving the nutritional value of maize-based flour, habitually used as the main ingredient in complementary foods.Despite the mushrooms' potential as an excellent source of vitamins and minerals with various health and nutritional benefits, it is still underutilized in combating undernutrition, particularly stunting and micronutrient deficiency common in Tanzania. Thus, this study aimed at investigating the effectiveness and suitability of oyster mushroom  were immediately packed in airtight polyethylene plastic bags and transported to the Food Science Laboratory at the Sokoine University of Agriculture, Morogoro, Tanzania. Maize samples were sorted to remove extraneous materials, winnowed, dehulled, and washed thoroughly with potable water to ensure complete removal of dust and unwanted materials. The latter was followed by solar drying of maize grains to a moisture content below 10%. Similarly, fresh oyster mushrooms were sorted, washed thoroughly with potable water, sliced, and solar-dried to a moisture content below 10%. Dried maize grains and mushrooms were milled using a hammer mill and heavy-duty blender, respectively, and sieved with 1 mm sieves to obtain fine flours. Maize and mushroom flours were then blended at ratios of 100 : 0, 70 : 30, 60 : 40, and 50 : 50 w/w). A porridge sample from white maize flour (100 : 0 maize : mushroom flour w/w) was prepared as a control. Porridge samples were prepared by mixing 350 g of flour in 1500 ml of portable boiling water. The mixture was left to boil on a gas cooker for 15 minutes with continuous stirring. Each sample of porridge was sweetened by the addition of 30 g of brown sugar.Three samples of porridges were prepared from three groups of blended maize-mushroom composite flours  of maize flour, oyster mushroom flour, and the blended maize-mushroom composite flour was performed using standard official analytical methods AOAC .2SO4 (10 g), CuSO4 (1 g), and selenium powder (0.1 g) was prepared and used as a Kjeltec catalyst. Afterwards, 10 ml of concentrated H2SO4 and Kjeltec catalyst was added in 1 g of each sample for digestion. The mixture was heated at 420°C for 2 hours to allow the digestion of the sample. About 10 ml of 0.5 NaOH was added in 10 ml of digested samples to provide a basic condition. Following the reaction, NH3 was collected as NH4OH in a conical flask containing 20 ml of 4% boric acid and a drop of modified methyl red as an indicator. Thereafter, the distillate was titrated against 0.1 N HCL solution until the endpoint was obtained. The percentage nitrogen in the sample was determined using the following expression:V1 is the titer for the sample (ml), V2 is the titer for blank (ml), V is the volume of diluted digest taken for distillation (10 ml), N is the normality of HCL solution, f is the factor for standard HCL solution, 0.014 is the milliequivalent weight of nitrogen, and S is the weight of the sample taken (g).The Kjeldahl method AOAC  was usedThe amount of crude protein in the sample was determined by multiplying the percentage nitrogen with 6.25 as a protein conversion factor using the following expression:W1 is the weight of the sample before extraction and W2 is the weight of the sample after extraction.The determination of crude fat in the sample was performed using standard procedure AOAC  with pet2SO4 and 0.31 N NaOH, boiled for 30 minutes, and washed with ethanol and petroleum ether twice. The residues obtained were then placed in clean, dry weighed crucibles and dried overnight at 100°C inside the moisture extraction oven. Thereafter, the crucibles were heated in a muffle furnace at 600°C for 6 hours, cooled, and weighed again. The weight differences of the crucibles were noted as crude fiber and calculated as percentage crude fiber as expressed as follows:W1 is the weight of the sample before heating, W2 is the weight of the sample after heating, and W3 is the weight of the original sample.The amount of crude fiber in each sample was determined using standard procedures of AOAC  describeW1 is the weight of empty crucible, W2 is the weight of the sample, and W3 is the weight of the heated sample and the crucible.The ash content in each sample was determined using the AOAC  standardW1 is the weight of the fresh sample (g) and W2 is the weight of the dry sample (g).Determination of moisture content in each sample was performed using the AOAC  standardThe percentage of moisture content (% MC) was used to obtain the dry matter content of the sample using the following equation:The content of carbohydrate in each sample was determined by the method described by Nielsen . The perThe energy value was determined using the method described by Farzana and Mohajan . For eacR is the absorbance reading in ppm, 100 is the volume of sample made, D.F is the dilution factor, 1000 is the conversion factor to mg/100 g, and S is the sample weight.The mineral  contents  of contrA total of 20 semitrained panel members comprised of nursing mothers and caregivers from Nambala Catholic Mission Dispensary in Arusha, Tanzania, were instructed to use the five-point hedonic scale for sensory evaluation of porridge. The coded maize flour porridge's sensory attributes as control and porridge from three complementary flour blend samples were evaluated using a five-point hedonic scale. The scale was in the range of 1: “dislike very much” and 5: “like very much” for the characteristics of colour, flavour, aroma texture, and general acceptability.n ≥ 3) were compared using the least significant difference (LSD) test (p < 0.05). All results are presented as the means ± standard deviation (SD) of multiple independent determinations.Experiments were conducted using a completely randomized design, and statistical analysis of data performed using the Statistical Package for the Social Sciences (SPSS version 20). Data were further subjected to one-way analysis of variance (ANOVA); the main treatment means calculated from the triplicate sample analyses (p ≤ 0.05), while the maize flour had a significantly higher content of crude fat, carbohydrate, and higher energy value. Similarly, formulated complementary flour blends had a significantly higher crude protein content, total ash, and crude fiber contents than those of control maize flour (p ≤ 0.05).The proximate analysis of maize flour, oyster mushroom flour, and formulated complementary flour blends is shown in An increase in protein content of formulated complementary flour blends highlights that blending maize flours with mushrooms increased the protein content. For instance, the blending of maize flour with 30%, 40%, and 50% mushroom flour increased protein content in formulated complementary flour blends by 18.20%, 20.37%, and 22.75%, respectively. The latter is expected since the mushroom flour had high amounts of protein compared to the maize flour. These results are in proximity to those reported by Ekunseitan et al. , who obsFurthermore, formulated complementary flour blends have the potential to meet the recommended daily intake (RDI) of protein from complementary foods which is 5.2 g/day at 6–8 months, 6.7 g/day at 9–11 months, and 9.1 g/day at 12–23 months of infants who are adequately breastfed . This RDAsh content of formulated flour blends increased with an increase in mushroom flour in formulated flour blends. Ash content increased significantly to 7.84%, 8.11%, and 8.65% in 70 : 30, 60 : 40, and 50 : 50 maize to mushroom flour blends. These results corroborate with Bamidele and Fasogbon , who repCrude fiber content increased to 15.13%, 16.73%, and 17.91% in 70 : 30, 60 : 40, and 50 : 50 maize to mushroom flour blends. The increase in ash and crude fiber contents observed in formulated flour blends could be attributed to the mushrooms' flour high fiber content. The fiber content results agree with Bamidele and Fasogbon , who repp ≥ 0.05) from maize flour's fat content (4.95%). The results have shown that mushrooms and maize flours could be blended quite well in the ratios of 30%, 40%, or 50% without altering the fat content present in maize flour. Mushrooms are comprised of low levels of unsaturated fats such as oleic and linoleic acids but very valuable to consumer healthy [Crude fat content ranged from 3.81% in 70 : 30 to 4.12% in 50 : 50 formulated complementary flour blends. These results were not significantly different .The carbohydrate content in formulated complementary flour blends decreased slightly, but significantly with the increase in oyster mushroom flour ratio in the blended flour. Carbohydrate content ranged from 37.39% to 45.46% in 70 : 30 and 50 : 50 blended maize-oyster mushroom flours, respectively . This coMoisture is a critical parameter to consider when accounting for the quality of flour and the acceptability of flour products. The latter is the determinant factor for shelf life and microbial growth during the storage of flour and flour products . In the The present study did not look at the safety of the formulated maize-oyster mushroom blended flour, which is highly susceptible to change during storage. Literature suggests that both maize and mushroom flours are generally vulnerable to rapid moisture uptake and discoloration. Consequently, this leads to mould growth when exposed to humid conditions, thus predisposing the product to loss of quality and safety to consumers . Nonetheless, documented literature also suggests that storage of maize, oyster, or blended flours in a paper bag, plastic bucket, or polyethylene bags under ambient and hot tropical weather conditions offers the chances of better shelf life stability of flour. Bamidele and Fasogbon  reportedThe mineral composition of white maize, oyster mushroom, and formulated complementary flour blends is presented in p ≤ 0.05) in zinc content between the maize (3.51 mg/100 g) and oyster mushroom flours (8.31 mg/100 g). For blended flours, the zinc content increased to 3.80, 4.12, and 4.54 mg/100 g after blending maize flour with 30%, 40%, or 50% of mushroom flour, respectively. The high content of zinc observed in oyster mushrooms could have increased the zinc content in blended maize-oyster mushroom flours. Friel et al. [There was a significant difference . The former and the latter were 4 and 6 times higher in oyster mushrooms than those observed in maize flour. Further results revealed that maize's blending with mushroom flour led to increased calcium and potassium contents in the blended flours . Certain antinutrients such as phytate, hydrocyanides, and tannin are present in mushrooms. Nonetheless, the reported levels of these antinutrients are low and unlikely to cause any significant effect on health or to the bioavailability of the nutrients in mushrooms . Additionally, Ijioma et al. (2015) reported that the consumer might not experience the toxic effect of antinutrients that might be present in complementary maize-oyster mushroom blended flours due to further destruction of these substances during cooking. Furthermore, studies have revealed that maize and oyster mushroom blending does not affect the bioavailability of micronutrients present in the blended flour. For instance, Regula et al. (2010) assessed iron bioavailability from cereal products enriched with dried mushrooms. They revealed that the addition of the mushroom significantly increased the bioavailability of iron in the products. This finding highlights that the blended maize-oyster mushroom complementary food increases the iron bioavailability to malnourished children, as suggested in the present study.p ≤ 0.05) in colour, flavour, aroma, texture, and overall acceptability between the control maize meal porridge and formulated complementary flour blends porridge was observed. Preference for colour, flavour, aroma, texture, and overall acceptability of samples was the highest in porridges prepared from the control maize meal flour. Formulated complementary foods developed from the three blended flours were relatively the least preferred. The porridges that were developed from 60 : 40 and 50 : 50 flour blends had relatively low ratings in most of the quality attributes, mainly colour, flavour, and aroma. Nonetheless, the panellists' assessment revealed both formulated complementary flour blends as significant.The sensory evaluation results of the porridges prepared from maize flour and formulated complementary flour blends are presented in Overall, the complementary foods developed from flour blends of maize and oyster mushrooms were not comparable to control  porridges. This could be attributed to the effect of oyster mushrooms on the flavour, aroma, and colour of the porridges developed from complementary flour blends. The formulated complementary flour blends were nutritionally improved through the enrichment with oyster mushroom, albeit there were some slight alterations in sensory attributes. Some reports revealed that enrichment of cereal flours with mushroom flour tends to decrease the sensory properties. Okafor et al.  observedThis study has demonstrated the nutritional value of oyster mushrooms, their effectiveness, and suitability for nutritional enrichment of habitual cereal-based complementary foods, especially maize flour, for breastfeeding children. The present results have revealed oyster mushroom as an ingredient of superior nutrient density compared to maize flour. The formulation of maize flour as the bulk ingredient, enriched with oyster mushroom, improved the nutritional quality of habitual maize-based complementary foods. However, the results have also shown that the blending of oyster mushroom with the maize meal could alter the complementary porridge's sensory properties . Overall, this study recommends blending oyster mushroom with maize flour to improve the nutritional content of formulated flour blend for young children who rely on maize porridge as their complementary food.


To recognize abnormal electroencephalogram (EEG) signals for epileptics, in this study, we proposed an online selective transfer TSK fuzzy classifier underlying joint distribution adaption and manifold regularization. Compared with most of the existing transfer classifiers, our classifier has its own characteristics: (1) the labeled EEG epochs from the source domain cannot accurately represent the primary EEG epochs in the target domain. Our classifier can make use of very few calibration data in the target domain to induce the target predictive function. (2) A joint distribution adaption is used to minimize the marginal distribution distance and the conditional distribution distance between the source domain and the target domain. (3) Clustering techniques are used to select source domains so that the computational complexity of our classifier is reduced. We construct six transfer scenarios based on the original EEG signals provided by the Bonn University to verify the performance of our classifier and introduce four baselines and a transfer support vector machine (SVM) for benchmarking studies. Experimental results indicate that our classifier wins the best performance and is not very sensitive to its parameters. The maturity of the brain–computer interface (BCI) technology has provided an important channel for the human to use artificial intelligence (AI) to explore the cognitive activities of the brain. For example, many AI methods have been proposed for an intelligent diagnosis of epilepsy instead of neurological physicians through electroencephalogram (EEG) signals  for epilepsy EEG signal recognition. First, it further explores the marginal probability distribution adaption between the source domain and the target domain from two aspects. One is that it additionally introduces conditional probability distribution adaption to further minimize the distribution difference. The second is that it preserves manifold consistency underlying the marginal probability distribution. Second, it can selectively leverage knowledge from multiple source domains.Data and Methods, we give the EEG data and our proposed method. In Results, we report the experimental results. Discussions about experimental results are presented in Discussions, and the whole conclusions are summarized in the last section.The following sections are organized as follows: in In this study, we download very commonly used epilepsy EEGThree feature extraction algorithms, that is, wavelet packet decomposition (WPD) Li, , short-tWavelet Packet DecompositionWavelet packet decomposition is used to extract time-frequency features from epilepsy EEG signals. More specifically, the epilepsy EEG signals are disassembled into six different frequency bands with the Daubechies 4 wavelet coefficients. Each band is considered as one feature. Short-Time Fourier TransformShort-time Fourier transform is used to extract frequency-domain features from epilepsy EEG signals. More specifically, the epilepsy EEG signals are disassembled into different local stationary signal segments, and then the Fourier transform is used to extract a group of spectra of the local segments, which are with evident time-varying characteristics at different times. Finally, six frequency bands are extracted from each group of spectra. Kernel Principal Component AnalysisKernel principal component analysis is used to extract time-domain features from epilepsy EEG signals. More specifically, the Gaussian function is chosen as the kernel to map the original features nonlinearly. Then six kinds of features are selected from the top six PC eigenvectors. We construct six online transfer scenarios from the EEG data after feature extraction . Each scM = 20 subject-specific objects from the target domain. The online calibration flowchart is shown in m0.In general, calibration in BCIs can be divided into two types, that is, offline calibration and online calibration . Lastly, we give the detailed algorithm steps of OS-JDA-MR-T-TSK-FC including how to select source domains.X, P(x)} in the transfer learning or domain adaption scenario consists of a d-dimensional feature space ∈ Rd and a marginal distribution P(x), and a task Γ = {Y, P(y|x)} in the similar scenario consists of a one-dimensional label space Y and a conditional distribution P(y|x), where y ∈ Y. Suppose that Ψs and Ψt are two domains derived from Ψ, they are deemed to be different when Xs ≠ Xt and/or Ps(x) ≠ Pt(x). Homoplastically, two tasks Γs and Γt derived from Γ are different when Ys ≠ Yt and/or Ps(y|x) ≠ Pt(y|x).A domain Ψ = {s having N-labeled EEG epochs t having M-labeled EEG subject-specific epochs s = Ψt, Ys = Yt, Ps(x) ≠ Pt(x), and Ps(y|x) ≠ Pt(y|x).Based on the above definitions, the target of OS-JDA-MR-T-TSK-FC is to train a predictive function on a source domain ΨOnline Transfer Learning FrameworkBecause the classic one-order TSK fuzzy classifier (1-TSK-FC)  for an unseen object x is formulated as the following form:k(x) is expressed asif parts, and then parts. Referring to the literature   in (2) as the following form:pg:pg to zero, that is, ∂Jorder−TSK−FS1−(pg)/∂pg = 0, we can compute pg analytically ast in the first term is the overall weights of the specific-subject objects. Generally, ωt should be larger than 1 so that more emphasis is given to objects in Ψs than Ψt. Therefore, we set ωt to ωt = max. λ1 and λ2 are regularization parameters. The first term contains two parts: the first is to measure the loss on Ψs, and the second is to measure the loss in Ψt. The second one is the joint distribution adaption term, and the third one is the manifold regularization term. Below, we will explain how to embody them formally.The . et al. . When cju et al.  and Zhanu et al. , we formObjective function of OS-JDA-MR-T-TSK-FCUnder the framework shown in (11), we specify each term to get the objective function of our online transfer TSK fuzzy classifier OS-JDA-MR-T-TSK-FC.s and Ψt; hence, the first term in (11) can be formulated asThe squared loss is taken as the loss function to measure the sum of squared training errors on both Ψs and Ψt are extracted in the same way, the joint distributions  between Ψs and Ψt are generally different. In order to meet practical requirements, we assume that Ps(x) ≠ Pt(x) and Ps(y|x) ≠ Pt(y|x). Therefore, a joint distribution adaptation should be designed to minimize the distribution similarity (distance) D between Ψs and Ψt.As all we know that even EEG epoch features in ΨD between Ψs and Ψt. As a result, D can be expressed ass,c belongs to Ψs and its objects are selected by {xi|xi ∈ Ψs ∧ yi = c}, and Ψt,c belongs to Ψt and its objects are selected by {xi|xi ∈ Ψt ∧ yi = c}, where c means the cth class in one domain. Also, for the source domain, Nc is used to denote the number of objects in the cth class, and for the specific-subject objects in the target domain, Mc is used to denote the number of objects in the cth class. Hence, D can be expressed asc is an MMD matrix defined as follows:D = D+D so that the joint distribution adaptation can be formulated asFirst, the projected MMD  and P(xj), then the corresponding Q(yi|ix) and Q(yj|xj) are considered as being similar. That is to say, for the objects in Ψs and the calibration objects in Ψt, if they are in a manifold, it is expected that their output  differences should be as small as possible. Therefore, the manifold regularization can be formulated as follows under geodesic smoothness,W = [wij]N+M)×(N+M)( is the graph affinity matrix in which each element is defined asν(xi) represents a set of v-nearest neighbors of object xi. L = [lij]N+M)×(N+M) by setting its derivative w.r.t pg to zero asBy substituting (14), (19), and (20) into our transfer learning framework shown in (12), we can obtain a transfer learning model, that is, OS-JDA-MR-T-TSK-FC asDifferent from most of the existing transfer models, OS-JDA-MR-T-TSK-FC can leverage knowledge from multiple source domains. However, as we know, too many source domains will improve computational complexity. Additionally, some source domains having significant differences with the target domain may bring some negative transfer knowledge. Therefore, according to Wu et al. , we adopvz,c to denote the mean vector of each class in the zth source domain, where z = 1,2,…, Z. Similarly, vt,c is used to denote the mean vector of each class in the target domain. The Euclidean distance between the zth source domain and the target domain can be computed asd, d, …, d} that contains Z domain distances. The distance set then is partitioned by k-means to k groups , and the source domains are selected from the cluster who has the smallest center.We use As a whole, the training of OS-JDA-MR-T-TSK-FC contains three parts: the first one is source domain selection, the second one is model training on a source domain combining with the target domain, and the last is classifier combination. Algorithm 1 shows the detailed training steps of OS-JDA-MR-T-TSK-FC.y from the space R to the space RC by that yij = 1 if y(xi) = j, and yij = 0 otherwise, where i = 1, 2, …, N + M, j = 1, 2, …, C, and C represents the number of classes. Thus, the label space becomes Rd+1 to Rd+1)×C. Its training set consists of the five source domains directly connected, and its testing set is the target domain. Therefore, BL1 is considered as a calibration-independent classifier, which does not use the subject-specific data in the target domain for training.Baseline 2 (BL2). It uses only subject-specific calibration EEG data in the target domain for training. Its testing set is the unlabeled data in the target domain. Therefore, BL2 is considered as a source domain-independent classifier, which does not consider the EEG data in the source domains at all.Baseline 3 (BL3). BL3 is trained on five training sets, receptively. Each set consisted of a source domain and the subject-specific data in the target domain. The five trained models are finally combined by a weight schema that is also used in Algorithm 1. Its testing set is the unlabeled data in the target domainTransfer support vector machine (TSVM) , λ1, and λ2 that should be fixed before a classification task. So, we should consider the robustness OS-JDA-MR-T-TSK-FC to them. The sensitivity analysis results are shown in From the objective function of OS-JDA-MR-T-TSK-FC, we see that there are three parameters, that is, ωWe observe from Moreover, the classification results in M, whereas the other four classifiers depend on M, and it is intuitive that they gradually perform better than BL1 with the increasing of M.BL1 does not use the specific-subject objects, so its accuracy is independent on M is set to 0. But BL1, BL3, TSVM, and OS-JDA-MR-T-TSK-FC can work because, except subject-specific objects, they also leverage training objects from the source domains. Compared with other algorithms, when M is too small, BL2 performs so badly because it cannot get enough training patterns from subject-specific objects.BL2 is only trained by the subject-specific objects. Therefore, BL2 becomes unusable when M is set to 0, TSVM always achieves the best performance. With the subject-specific objects gradually added into the training set, OS-JDA-MR-T-TSK-FC soon performs better than TSVM, which indicates that significant differences exist among the domains. Hence, a domain-dependent classifier, for example, TSVM is not very expected in our online transfer scenarios.When When one batch (four subject-specific objects are taken as a batch in our experiments) or at most two batches of subject-specific objects are added into the training set, the classification performance of OS-JDA-MR-T-TSK-FC becomes stable. That is to say, the number of subject-specific objects OS-JDA-MR-T-TSK-FC needs is very small. So, OS-JDA-MR-T-TSK-FC meets the practical requirements because subject-specific objects are very few in real-world applications.x1 is In addition to classification performance, interpretability is also a main characteristic of the proposed OS-JDA-MR-T-TSK-FC. From If the energy of an EEG signal band (band 1) is “high,” and the energy of an EEG signal band (band 2) is “a little low,” and the energy of an EEG signal band (band 3) is “low,” and the energy of an EEG signal band (band 4) is “low,” and the energy of an EEG signal band (band 5) is “low,” and the energy of an EEG signal band (band 6) is “low,”thenthe consequent of the first fuzzy rule can be expressed as:x1+0.4452x2−0.5342x3+0.2342x4−0.9734x5−0.3244x6.1 in the range of (Geng et al., 2 in the range of (Ghosh-Dastidar et al., From In this study, we propose a seizure classification model OS-JDA-MR-T-TSK-FC using an online selective transfer TSK fuzzy classifier with a joint distribution adaption and manifold regularization. We use epilepsy EEG signals provided by the University of Bonn as the original data and construct six transfer scenarios in three kinds of feature spaces to demonstrate the promising performance of OS-JDA-MR-T-TSK-FC. We also generate four baselines and introduce a transfer SVM model for fair comparison. The experimental results show that OS-JDA-MR-T-TSK-FC performs better than baselines and the introduced two transfer models. However, in this study, we only consider how to select the source domains. Recent studies show that dynamically selecting useful samples from the source domain can effectively induce the learning on the target domain. Therefore, in our future work, we will try to develop a mechanism, for example, classification error consensus to select most useful samples from the source domain.http://www.meb.unibonn.de/epileptologie/science/physik/eegdata.html.The original EEG data are available in YZ designed the whole algorithm and experiments. ZZ, HB, and WL contributed on code implementation, and LW gave some suggestions to the writing.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


In order to produce biscuits from off‐season sorghum, a local “Muskwari” sorghum was milled and sieved. This flour was used to produce shortbread biscuits with different substitutions rates of wheat flour to that of sorghum. The standard formulation of this same type of shortbread biscuits was used and biscuits were produced with incorporation rates of wheat flour to that of sorghum, from 0% to 100%, with a gap of 10 between two consecutives percentages. The technological characterization of the sorghum flour produced indicates a good water absorption capacity, and interesting solubility index and swelling rate. Technological aspect indicated that by changing speed and kneading time, resting the dough, it is possible to produce 100% sorghum flour shortbread biscuits. Shortbread biscuits made from 70% of wheat flour incorporation had the best average scores for overall preference criteria (6.97 ± 1.30), color (7.1 ± 1.45), and texture (6.62 ± 1.54). For smell and taste criteria, the 40% biscuits and the witness received the highest average scores, respectively, namely 6.77 ± 1.55 for smell and 7.12 ± 1.29 for taste. Analysis of the nutritional and energy intake of the control biscuit and the 70% substitution revealed that between the two, the latter had a significantly higher intake of total carbohydrates (58.51 g), dietary fiber (2.15 g), and total energy (454.1 kcal In order to produce shortbread biscuits from off‐season sorghum, a local “Muskwari” sorghum was milled and sieved. The obtained flour was of 0.5 mm grain size. This flour was used to produce shortbread biscuits with different substitutions rates of wheat flour to that of sorghum. The means and standard deviations of the results obtained for each parameter and for each flour are recorded in Table The difference recorded between the water absorption capacities of these two flours is probably related to the physicochemical characteristics of its constituents. Indeed, the water absorption capacities is an essential technological parameter to control the consistency of the dough  as in the production of these 100% sorghum flour biscuits, then the distribution of water within the grain is uneven (poor starch hydration capacity). Crystallites near water‐rich amorphous zones would gelatinize while others would melt at higher temperatures, until only a single‐grain melting occurred . At the significance level of 5%, the analysis of variances in multiple comparison of the scores assigned to the different substitution rates allowed us to obtain the results presented in Figure Biscuits with 70% wheat flour incorporation had the highest average scores for the overall preference criteria (6.97 ± 1.30), color 7.1 ± 1.45), and texture (6.62 ± 1.54). For the odor and taste criteria, the 60% biscuits and the control received the highest average scores, namely 6.77 ± 1.55 for odor and 7.12 ± 1.29 for taste. Similar results were observed during the work of Akintayo and Sedgo  and IFAD5, and teThis analysis of the variances shows us that, apart from T7 and T8, a significant difference is observed only between two substitution rates separated by at least two substitution steps . This insignificant difference between two consecutive substitution rates may be due here to the fact that sorghum and wheat flours, like the flours of most cereals, do not have “of taste” characteristics. It could indicate a good choice made at the level of substitution, good conduct of the operations of production of biscuits and the level of sensory tests, the bias from the tasters.3.3.2The proximate comparative nutritional composition of the 100% wheat flour biscuit and the one most appreciated substituted biscuit by panelists (70% substitution) is given in Table Similar energy intakes  were observed for the 20% sorghum biscuits produced by Akintayo and Sedgo , during 4Madjéri sorghum grains. The technological characterization of this flour allowed us to notice that it had poor hydration properties, with a water absorption capacity of 102.26 ± 6.41% and a solubility index of 20 ± 5, 25%. The 100% sorghum flour biscuits produced by changing the kneading time and incorporating the resting time of the dough in the process of making shortbread type biscuits were considered to be of poor technological quality. Because of its high gluten content, the partial substitution of sorghum flour with that of wheat in the biscuit formulation may improve technological properties such as lightness and friability. Up to 30% substitution, biscuits remain of poor technological quality.This work aims at valorizing a local sorghum produced in Cameroon by producing biscuits. Sorghum flour was produced from Panelists preferred the 70% substituted sorghum flour biscuit. It also appears from this study that the biscuit at 70% sorghum flour preferred by the panelists is more energetic than biscuit at 100% wheat flour. This can lead to a light and rich biscuits that can add value to local grains while meeting new needs for light and rich food in urban areas.Figure S1‐S2Click here for additional data file.