Miracle-dz/UniFAR-FTUs huggingface dataset:
A Chimera of Th1 Stimulatory Proteins of Leishmania donovani Offers Moderate Immunotherapeutic Efficacy with a Th1-Inclined Immune Response against Visceral Leishmaniasis

Immunotherapy, a treatment based on host immune system activation, has been shown to provide a substitute for marginally effective conventional chemotherapy in controlling visceral leishmaniasis (VL), the deadliest form of leishmaniasis. As the majority of endemic inhabitants exhibit either subclinical or asymptomatic infection which often develops into the active disease state, therapeutic intervention seems to be an important avenue for combating infections by stimulating the natural defense system of infected individuals. With this perspective, the present study focuses on two immunodominant Leishmania (L.) donovani antigens (triosephosphate isomerase and enolase) previously proved to be potent prophylactic VL vaccine candidates, for generating a recombinant chimeric antigen. This is based on the premise that in a heterogeneous population, a multivalent antigen vaccine would be required for an effective response against leishmaniasis (a complex parasitic disease). The resulting molecule rLdT-E chimeric protein was evaluated for its immunogenicity and immunotherapeutic efficacy. A Th1 stimulating adjuvant BCG was employed with the protein which showed a remarkable 70% inhibition of splenic parasitic multiplication positively correlated with boosted Th1 dominant immune response against lethal L. donovani challenge in hamsters as evidenced by high IFN-γ and TNF-α and low IL-10. In addition, immunological analysis of antibody subclass presented IgG2-based humoral response besides considerable delayed-type hypersensitivity and lymphocyte proliferative responses in rLdT-E/BCG-treated animals. Our observations indicate the potential of the chimera towards its candidature for an effective vaccine against Leishmania donovani infection.
Modeling Study on the Solder Joint Reliability of a Leadframe Package under Powered Thermal Cycling

This paper aims to present a thermo-mechanical modeling approach to predict the solder joint reliability of a leadframe-based package under powered thermal cycling (PTC) test from -40 o C to 105C. The study involves modeling the PTC condition as a standard thermal cycling with a modified temperature boundary to account for the temperature increase due to the applied power to the device package mounted on board. The temperature ramp and dwell times were maintained. Based on the finite element analysis (FEA) results and comparison with actual data, modeling a PTC as a modified thermal cycling process provides a good prediction of the solder joint life. The analysis is simpler and would be beneficial for getting quick assessments of new leadframe package designs.
Conversion Kinetics of Silicate, Borosilicate, and Borate Bioactive Glasses to Hydroxyapatite

Bioactive 45S5 glass has been studied extensively both in vivo and in vitro, and it is relatively well known that when placed in a phosphate containing solution the glass will react to form the bone-like material hydroxyapatite (HA). In the present work, a kinetic analysis of previously measured weight loss data was done to determine reaction rate constants for four bioactive glasses; one silicate glass, two borosilicate glasses, and one borate glass, via the contracting volume model. The reaction rate increased with increasing B(2)O(3) content. , with the borate glass reacting nearly five times faster than the silicate 45S5 glass. The three silica containing glasses all deviated from the contracting volume model after approximately 50-70% of the total weight loss; however, when compared to the 3D diffusion model, the normalised data were in good agreement to 100% of the total weight loss. The deviation from the contracting volume model to the slower 3D diffusion model indicates a change in conversion model for the silica containing glasses and can likely be attributed to the formation of a silica rich layer of a certain thickness that began controlling the release of ions from the unreacted glass by diffusion.
Huge Instability of Pt/C Catalysts in Alkaline Medium

The stability of carbon-supported electrocatalysts has been largely investigated in acidic electrolytes, but the literature is much scarcer regarding similar stability studies in alkaline medium. Herein, the degradation of Vulcan XC-72-supported platinum nanoparticles (noted Pt/C), a state-of-the-art proton exchange membrane fuel cell electrocatalyst, is investigated in alkaline medium by combining electrochemical measurements and identical location transmission electron microscopy; electrochemical surface area (ECSA) losses were bridged to electrocatalyst morphological changes. The results demonstrate that the degradation in 0.1 M NaOH at 25 °C is severe (60% of ECSA loss after only 150 cycles between 0.1 and 1.23 V vs RHE), which is about 3 times worse than in acidic media for this soft accelerated stress test. Severe carbon corrosion has been ruled out according to Raman spectroscopy and X-ray photoelectron spectroscopy measurements, and it seems that the chemistry of the carbon support (in particular,.
Performances of some high dimensional regression methods

Abstract Variable selection is one of the important practical issues for many scientific areas, particularly in chemometrics, where data sets include several hundreds of variables and low number of observations. The aim of this paper is to compare some newly proposed variable selection methods by means of extensive simulation studies and to give some practical hints for use of the compared methods. Furthermore, we underpin the performances of compared methods based on real data examples.
Polycyclic Aromatic Hydrocarbons in PM 2.5 and PM10 From Industrial Area of Odisha, India: Sources, Atmospheric Transport and Health Risk Assessment

In this study we aim to assess 16 priority PAHs enlisted by the US Environmental Protection Agency in PM 2.5 and PM 10 for the first time from industrial areas of Odisha State in India. During 2017–2018, bimonthly sampling of PM 10 and PM 2.5 were carried out for 24 hours by respirable dust sampler and PM 2.5 sampler respectively, in the industrial and mining areas of Jharsuguda (n = 2) and Angul (n = 4) during the pre-monsoon, monsoon and post monsoonal seasons. Highest average concentration of ∑ 16 PAHs in PM 2.5 was observed during post monsoon (170 ng/m3) followed by pre-monsoon (17–89 ng/m3; avg, 48 ng/m3) and monsoonal season (2–40 ng/m3 ; avg, 16 ng/m 3 ), respectively. Similar trend of ∑ 16 PAHs levels in PM 10 was seen with higher levels during post monsoon (116–471 ng/m3; avg, 286 ng/m3) followed by pre-monsoon (avg, 81 ng/m3) and monsoon seasons (27 ng/m3. Diagnostic ratios BaA/(BaA + Chry), Phe/(Phe + Ant) and Flt/(Flt + Pyr) and principal component analysis (PCA) suggest diesel, gasoline and coal combustion are the major contributors for atmospheric PAHs pollution in Odisha. Back trajectories analysis revealed that PAHs concentration was affected majorly by air masses originating from the northwest direction traversing through central India. Toxic equivalents (TEQs) ranged between 0.24 to 94.13 ng TEQ/m3. In our study incremental lifetime cancer risk (ILCR) ranged between 10 − 5 and 10 − 3 representing potential cancer risk.
Physiologic specialization of Puccinia triticina, the causal agent of wheat leaf rust, in Canada in 2015–2019

Abstract Wheat leaves infected with Puccinia triticina, the causal agent of wheat leaf rust, were collected annually throughout Canada from 2015 to 2019. There were 47, 75, 44, 38 and 54 different virulence phenotypes, respectively, found annually, representing 154 unique virulence phenotypes. From Alberta, there were three virulence phenotypes, MBDS, TDBJ, and TDBS, found in 2015 and eight in 2019, the most common being MBDS and TNBJ (both 20%). The most common virulence phenotypes found in Manitoba and Saskatchewan were MBDS (17.8%) and TNBG (16.3%) in 2015, MNPS (17.2%) and MBDS (15.9%) in 2016, MNPS (41.9%) and TBBG (17.2%) in 2017, MNPS (35.3%) and TBBG (34.8%) in 2018, and MNPS (54.7%) and MBDS (10.7%) in 2019. In Ontario, the most common virulence phenotypes found were MBTN (25%) and MBDS (16.7%) in 2015, MCQQ (13.6%) in 2016, MBTN (33.3%) and PBDG (19.0%) in 2017, TFPJ (13.6%) in 2018, and MCTN (14.5%) and MBTN (10.9%) in 2019. In Quebec the most common virulence phenotypes found were TBBG (66.7%) and MLDS (33.3%) in 2015, TCGJ (23.1%) and MBTN (15.4%) in 2017, MCQH (26.3%) and FCPT (21.1%) in 2018, and MBTN and MCRS (both 18.2%) in 2019. The frequencies of virulence varied on all resistance genes over these years. Within Canada, virulence on Lr21 peaked in 2018 at 39.9% and then declined in 2019, with a similar trend noticed for virulence on Lr2a and Lr2c. There was no virulence detected on Lr19, Lr29, Lr32, Lr52, and Lr22a, while virulence on Lr25 was rare.
Design of A Parallel Decoding Method for LDPC Code Generated via Primitive Polynomial

An effective way of improving decoding performance of an LDPC code is to extend the single-decoder decoding method to a parallel decoding method with multiple sub-decoders. To this end, this paper proposes a parallel decoding method for the LDPC codes constructed by m-sequence. In this method, the sub-decoders have two types. The first one contains only one decoding module using the original parity-check constraints to implement a belief propagation (BP) algorithm. The second one consists of a pre-decode module and a decoding module. The parity-check matrices for pre-decode modules are generated by the parity-check constraints of the sub-sequences sampled from an m-sequence. Then, the number of iterations of the BP process in each pre-decode module is set as half of the girth of the parity-check matrix, resulting in the elimination of the impact of short cycles. Using maximum a posterior (MAP), the least metric selector (LMS) finally picks out a codeword from the outputs of sub-decoders. Our simulation results show that the performance gain of the proposed parallel decoding method with five sub-decoders is about 0.4 dB, compared to the single-decoder decoding method at the bit error rate (BER) of 10−5.
Impact of Chemotherapy-Induced Peripheral Neuropathy on Quality of Life in Patients with Advanced Lung Cancer Receiving Platinum-Based Chemotherapy

Chemotherapy-induced peripheral neuropathy (CIPN) is a common adverse effect of neurotoxic anticancer drugs that may affect quality of life (QoL). Purpose: The purposes of this study were to: assess the levels of CIPN, anxiety, depression, CIPN–related QoL, and general QoL; and identify the factors related to CIPN–related QoL and general QoL in patients with advanced lung cancer (LC) receiving platinum-based chemotherapy. This cross-sectional study examined patients with advanced LC who received platinum-based chemotherapy from the thoracic oncology inpatient wards of a medical center in northern Taiwan. Structured questionnaires were used to measure patients’ CIPN (European Organization for Research and Treatment of Cancer quality of life questionnaire–chemotherapy–induced peripheral neuropathy 20), anxiety (Hospital Anxiety and Depression Scale Depression Scale [HADS]), depression (HADS), CIPN-related QoL (Functional Assessment of Cancer Therapy /Gynecologic Oncology Group-Neurotoxicity subscale [FACT/GOG–Ntx]), and general QoL (Functional Assessment of Cancer Therapy–General Input [FACT-G]). Of 93 patients with advanced LC, 53.8% reported CIPN–sensory impairment and 47.3% reported CIPN–motor impairment. The most common CIPN symptoms were difficulty getting or maintaining an erection (only for men > 65 years) and difficulty in climbing stairs or getting up out of a chair. Poor CIPN–related QoL (FACT/GOG–Ntx) was associated with more CIPN–sensory and more CIPN–motor impairment. Poor general QoL (FACT-G) was associated with a higher level of depression, a higher level of anxiety, and receipt of more chemotherapy cycles. More than half of LC patients report impairment related to CIPN, calling for holistic treatment to improve QoL.
Prevalence and Characterization of Biallelic and Monoallelic NTHL1 and MSH3 Variant Carriers From a Pan-Cancer Patient Population

PURPOSE NTHL1 and MSH3 have been implicated as autosomal recessive cancer predisposition genes. Although individuals with biallelic NTHL1 and MSH3 pathogenic variants (PVs) have increased cancer and polyposis risk, risks for monoallelic carriers are uncertain. We sought to assess the prevalence and characterize NTHL1 and MSH3 from a large pan-cancer patient population. MATERIALS AND METHODS Patients with pan-cancer (n = 11,081) underwent matched tumor-normal sequencing with consent for germline analysis. Medical records and tumors were reviewed and analyzed. Prevalence of PVs was compared with reference controls (Genome Aggregation Database). RESULTS NTHL1-PVs were identified in 40 patients including 39 monoallelic carriers (39/11,081 = 0.35%) and one with biallelic variants (1/11,081 = 0.009%) and a diagnosis of isolated early-onset breast cancer. NTHL1-associated mutational signature 30 was identified in the tumors of the biallelic patient and two carriers. Colonic polyposis was not identified in any NTHL1 patient. MSH3-PVs were identified in 13 patients, including 12 monoallelic carriers (12/11,081 = 0.11%) and one with biallelic MSH3 variants (1/11,081 = 0.009%) and diagnoses of later-onset cancers, attenuated polyposis, and abnormal MSH3-protein expression. Of the 12 MSH3 carriers, two had early-onset cancer diagnoses with tumor loss of heterozygosity of the wild-type MSH3 allele. Ancestry-specific burden tests demonstrated that NTHL1 and MSH3 prevalence was not significantly different in this pan-cancer population versus controls. CONCLUSION NTHL1 and MSH3 germline alterations were not enriched in this pan-cancer patient population. However, tumor-specific findings, such as mutational signature 30 and loss of heterozygosity of the wild-type allele, suggest the potential contribution of monoallelic variants to tumorigenesis in a subset of patients.
Overview of the French Operational Network for In Situ Observation of PM Chemical Composition and Sources in Urban Environments (CARA Program)

The CARA program has been running since 2008 by the French reference laboratory for air quality monitoring (LCSQA) and the regional monitoring networks, to gain better knowledge—at a national level—on particulate matter (PM) chemistry and its diverse origins in urban environments. It results in strong collaborations with international-level academic partners for state-of-the-art, straightforward, and robust results and methodologies within operational air quality stakeholders (and subsequently, decision makers). Here, we illustrate some of the main outputs obtained over the last decade, thanks to this program, regarding methodological aspects (both in terms of measurement techniques and data treatment procedures) as well as acquired knowledge on the predominant PM sources. Offline and online methods are used following well-suited quality assurance and quality control procedures, notably including inter-laboratory comparison exercises. Source apportionment studies are conducted using various receptor modeling approaches. Overall, the results presented herewith underline the major influences of residential wood burning (during the cold period) and road transport emissions (exhaust and non-exhaust ones, all throughout the year), as well as substantial contributions of mineral dust and primary biogenic particles (mostly during the warm period). Long-range transport phenomena, e.g., advection of secondary inorganic aerosols from the European continental sector and of Saharan dust into the French West Indies, are also discussed in this paper. Finally, we briefly address the use of stable isotope measurements (δ15N) and of various organic molecular markers for a better understanding of the origins of ammonium and of the different organic aerosol fractions, respectively.
Autonomous Vehicle Safe Operating Speeds on the Automated Skyway Express in Jacksonville, Florida

Autonomous vehicles (AV) differ significantly from traditional passenger vehicles in both their behavior and physical characteristics. As such, the validity of the guidance provided in the Manual for Assessing Safety Hardware, Second Edition (MASH 2016) is questionable in AV applications. Impact angles, speeds, and vehicle weights specified in MASH 2016 are inextricably linked to the traditional vehicles underlying the estimates. For AV applications, these parameters must be estimated from the ground up, stepping outside the guidance of MASH 2016. In this paper, a conservative method for evaluating existing infrastructure to support AV traffic is proposed. The method integrates traditional structural analyses with unconventional methods of estimating impact conditions. This methodology was developed for the Jacksonville Transportation Authority, who, when faced with unique challenges in maintaining and expanding their Automated Skyway Express, opted to convert the system from monorail to AV traffic. Leading AV developers were surveyed to develop a portfolio of potential candidates for the conversion. Estimated impact conditions were then compared against the capacity of the system’s existing concrete parapets. Ultimately, safe operating speeds for each AV candidate were recommended on the bases of structural capacity and vehicle stability. All but one AV candidate were deemed capable of safely operating at the desired speed of 25 mph without any modifications to the barrier. Although the methodology was developed for a particular case, it is applicable to future implementations of AVs on existing infrastructure, provided the roadway is confined similarly to the Skyway deck.
Black Box Warning Did Not Cause Increased Suicides

In their article “Increases in suicide deaths among adolescents and young adults following US Food and Drug Administration antidepressant boxed warnings and declines in depression care” Lu et al. claimed that the suicidality Black Box Warning for antidepressants led to decreased treatment of depression, which caused a high number of excess suicides among adolescents and young adults in the United States (1).
Investigation of Model for Initial Phase of Communication

We propose an agent model that determines its behavior from an internal state and a spatial relationship with a target to generate approaching and avoiding behaviors in encounter scenes. This model is based on the relationship with an opponent rather than with a scenario. The agent moves to increase the utility value obtained from the preferences for both aggressive and passive involvement. We analyzed the behavioral and utterance data of human–human interactions based only on two-dimensional position information by simple-shaped robots. The rate of participants’ behavior following the model was significantly higher than that of a random walker. Based on this result, we estimated the internal state during the interactions from the behavior of the participants and analyzed it. The words uttered by one member of a pair correlated with the internal state estimated from the behavior of the other member of the pair. The frequency of the internal states observed from the participants who were recommended to interact with the partner was different from that observed from the participants who did not receive such recommendations. These results suggest that a model with two preferences can approximate a human’s internal state in encounter scenes.
Align R-CNN: A Pairwise Head Network for Visual Relationship Detection

Scene graphs connect individual objects with visual relationships. They serve as a comprehensive scene representation for downstream multimodal tasks. However, by exploring recent progress in Scene Graph Generation (SGG), we find that the performance of recent works is highly limited by the pairwise relationship modeling by naive feature concatenation. Such pairwise features lack sufficient object interaction due to the mis-aligned object parts, resulting in non-discriminative pairwise features for visual relationship prediction. For example, naive concatenated pairwise feature usually make the model fail to discriminate between riding and feeding for object pair person and horse. To this end, we design a meta-architecture— learning-to-align — for dynamic object feature concatenation. We call our model: Align R-CNN. Specifically, we introduce a novel attention-based multiple region alignment module that can be jointly optimized with SGG. Experiments on the large-scale SGG benchmark Visual Genome show that the proposed Align R-CNN can replace the naive feature concatenation and thus boost all the existing SGG methods.
Mapping Spatial Distribution of Pores in an Additively Manufactured Gold Alloy Using Neutron Microtomography

A crucial criterion for the quality of the additively manufactured parts is the porosity content for achieving an acceptable final relative density. In addition, for jewelry applications, visible pores are unacceptable at or in the vicinity of the surface. In this study, non-destructive 3D neutron microtomography is applied to map the spatial distribution of pores in additively manufactured red-gold samples. The 3D imaging assessment underlines the high relative density of the printed red-gold sample and indicates residual pore sizes are predominantly below the limit of concern for jewelry applications. The 3D maps of pores within printed samples highlight the effect of the scanning strategy on the final quality and location of pores in the printed samples. These results confirm that neutron microtomography is a novel and precise tool to characterize residual porosity in additively manufactured gold alloys and other higher-Z materials where such investigation using other non-destructive methods (such as X-rays) is challenging due to the limited penetration depth.
Enhancing Work Performance of Extension Agents among Cocoa Farmers in Malaysia: The Influence of Human Resource Development Skills

This study examines the relationships between human resource development skills (leadership, decision making support, and social skills) with the work performance of extension agents among cocoa farmers in Malaysia. The study used stratified sampling technique to select 668 cocoa farmers who were exposed to extension programs facilitated by extension agents of the Malaysian Cocoa Board in 3 regions of Malaysia. The data were analyzed using descriptive statistics, correlation, and regression analyses. The results show that cocoa farmers rated level of work performance, leadership, decision making support, and social skills as high. Significant and positive correlation (p < 0.01) existed between each variable and work performance. Regression analysis results showed that leadership skill, decision making support skill, and social skill were significant predictors to enhance work performance. The R2 value of 0.564 indicates that the 3 skills gave 56.4 % explanation of the variance in extension agents’ work performance. The results also suggested that decision making support skill (β = 0.321) was the most important factor that influenced work performance, followed by leadership skill and social skill. Hence, decision making support skill, leadership skill, and social skill should be taken into consideration in enhancing work performance, especially among farmers and the extension agents who work with them, for continuous performance improvement in their work. The skills that have been identified in this study can be integrated into both the pre-service and in-service training and development of extension agents in their line of work to improve their skills in sharing new technology.