Miracle-dz/UniFAR-FTUs huggingface dataset:
Rice Farmers' Knowledge of the Risks of Pesticide Use in Bangladesh

Background. Population growth has led to the need to increase global food production. Pesticides are an important tool used in efforts to control insect pests. About 20–30% of agricultural produce is lost annually due to insect pests, diseases, weeds and rodents. While pesticides are effective against pest populations, if used injudiciously, they may pose health hazards to humans, domestic animals, natural enemies of crop pests and other forms of life through unwanted contamination of food, feed, water bodies and the environment. Objectives. The aim of the present study was to examine farmers' level of knowledge and awareness of environmental pollution due to unsafe use of pesticides for controlling rice pests and to explore ways of reducing their usage. Methods. The research population consisted of 120 rice farmers: 40 farmers randomly selected from each of the three rice growing districts of Bangladesh; Mymensingh, Tangail and Jamalpur. Data was collected through group discussions, direct observations and personal interviews during March 2013 to May 2014. Results. Farmers mainly sought advice on pesticide use from pesticide dealers or retailers and a very few farmers contacted government extension workers for this purpose. Most of the farmers had an understanding of natural enemies of rice pests and that the application of synthetic insecticides in the field can reduce their population. A few farmers followed integrated pest management (IPM) practices with little understanding of the adverse effects of insecticides on the environment and ecosystem. The majority of farmers understood the harmful effects of pesticides on health of human and animals, beneficial species, fish, insect resistance, soil and food. It was also found that education on pest management, information through television, more contact with extension personnel and farmers' awareness of IPM were critical factors for improving rice farmers' understanding of the ecological hazards caused by overuse of pesticides. Most of the farmers suggested that timely removal of weeds, appropriate timing for pesticide application, balanced doses of fertilizers, pest monitoring, correct dose of appropriate pesticides, pest tolerant varieties, increasing technical knowledge and skills and creating social awareness of environmental pollution among farmers were necessary to reduce the quantity of pesticides and minimize environmental hazards. Conclusions. The present study identified a need to intensify farmers' awareness and knowledge of integrated pest management and environmental pollution through extension organizations which could help promote sustainable agricultural development and improve the currently endangered bio-diversity of Bangladesh. Participant Consent. Obtained Ethical Approval. This study was approved by the PhD Supervisory Committee assigned by the Department of Entomology of Bangladesh Agricultural University. Competing Interests. The authors declare no competing financial interests
A case of prolonged generalized exanthematous pustulosis caused by hydroxychloroquine—Literature review

Acute generalized exanthematous pustulosis (AGEP) is a self‐limited drug reaction. Hydroxychloroquine (HCQ) is an uncommon cause of AGEP with a prolonged recovery course; Thus, the physicians should take the possibility of this rare but severe event in their minds and try to diagnose correctly and better management.
Scalable Block-Wise Product BCH Codes

In this paper we comprehensively investigate block-wise product (BWP) BCH codes, wherein raw data is arranged in the form of block-wise matrix and each row and column BCH codes intersect on one data block. We first devise efficient BCH decoding algorithms, including reduced-1-bit decoding, extra-1-bit list decoding, and extra-2-bit list decoding. We next present a systematic construction of BWP-BCH codes upon given message and parity lengths that takes into account for performance, implementation and scalability, rather than focusing on a regularly defined BWP-BCH code. It can easily accommodate different message length or parity length at minimal changes. It employs extended BCH codes instead of BCH codes to reduce miscorrection rate and an inner RS code to lower error floor. We also describe a high-speed scalable encoder. We finally present a novel iterative decoding algorithm which is divided into three phases. The first phase iteratively applies reduced BCH correction capabilities to correct lightly corrupted rows/columns while suppressing miscorrection, until the process stalls. The second phase iteratively decodes up to the designed correction capabilities, until the process stalls. The last phase iteratively applies the proposed list decoding in a novel manner which effectively determines the correct candidate. The key idea is to use cross decoding upon each list candidate to pick the candidate which enables the maximum number of successful cross decoding. Our simulations show that the proposed algorithm provides a significant performance boost compared to the state-of-the-art algorithms.
Structural and energetic basis for the inhibitory selectivity of both catalytic domains of dimeric HDAC6

Abstract HDAC6 is a protein involved in cancer, neurodegenerative disease and inflammatory disorders. To date, the full three-dimensional (3D) structure of human HDAC6 has not been elucidated; however, there are some experimental 3D structural homologs to HDAC6 that can be used as templates. In this work, we utilized molecular modeling procedures to model both of the catalytic domains of HDAC6 connected by the linker region where DMB region is placed. Once the 3D structure of human HDAC6 was obtained, it was structurally evaluated and submitted to docking and molecular dynamic (MD) simulations along with Molecular Mechanics/Generalized Born Surface Area (MM/GBSA) method to explore the stability and the binding free energy properties of the HDAC6–ligand complexes. In addition, its structural and energetic behavior was explored with each one of the catalytic domains in the molecular recognition of six selective HDAC6 inhibitors, HPOB, CAY10603, Nexturastat, Rocilinostat, Tubacin and Tubastatin A for DD2, and with the so-called 9-peptide which is DD1–HDAC6 selective substrate. The use of the whole system (DD1–DMB–DD2) showed a tendency toward the ligand affinity of DD2, CAY10603> Tubacin > Rocilinostat > Nexturastat > HPOB > Tubastatin > 9-peptide, which is in line with experimental reports. However, 9-peptide showed a higher affinity for DD1, which agrees with experimental reports elsewhere. Principal component analysis provided important information about the structural changes linked to the molecular recognition process, whereas per-residue decomposition analysis revealed the energetic contribution of the key residues in the molecular binding and structural characteristics that could assist in drug design.
Applicability of a 3D Laser Scanner for Characterizing the Spray Distribution Pattern of an Air-Assisted Sprayer

Three-dimensional (3D) laser technology has been tested for assessing the performance of air-assisted spraying. A static test using an air-assisted sprayer equipped with two axial fans (front and back) with opposing directions of rotation was developed. The sprayer was adjusted to spread water in a static mode, at a pressure of 10 bars, with four air volumetric flow rates. Measurements were performed using a Leica HDS6000 3D laser scanner. In addition, the flow and velocity of air generated by the air-assisted sprayer were measured using a hot-wire anemometer and a 3D sonic anemometer with the objective of estimating the influence of air flow on the spatial distribution of spray droplets. To carry out the analysis, all of the droplets detected by the laser were considered to be of the same size. The distribution of products was asymmetric when the machine only worked with the back fan, with 41% of the product distributed on the left side versus 59% on the right side, as referenced to the direction of the machine’s advance. This asymmetry was corrected when the machine functioned with the two fans activated. These spray data were concordant with the measured air flow generated by the machine in the different working conditions. For the different regulation settings of the machine, taking the vertical of the machine as 0°, the angular region comprised between 40° and 60° was the one that received the highest quantity of product. The increase of the air flow produced a greater distance of the product. For the highest air flow configuration, 99% of the product detected by the laser was detected within a distance of 16 m from the axis of the machine.
Efficacy of long‐term oral telmisartan treatment in cats with hypertension: Results of a prospective European clinical trial

Background Efficacy of telmisartan in treating hypertension (HT) in cats has not been largely investigated. Objective Telmisartan oral solution effectively controls systolic arterial blood pressure (SABP) in hypertensive cats. Animals Two‐hundred eighty‐five client‐owned cats with systemic HT. Methods Prospective, multicenter, placebo‐controlled, randomized, double‐blinded study. Hypertensive cats diagnosed with SABP ≥160 mmHg and ≤200 mmHg without target‐organ‐damage were randomized (2 : 1 ratio) to receive 2 mg/kg telmisartan or placebo q24 PO. A 28‐day efficacy phase was followed by a 120‐day extended use phase. Efficacy was defined as significant difference in mean SABP reduction between telmisartan and placebo on Day 14 and group mean reduction in SABP of > 20 mmHg by telmisartan on Day 28 compared to baseline. Results Two‐hundred fifty‐two cats completed the efficacy and 144 cats the extended use phases. Mean SABP reduction at Day 14 differed significantly between groups (P < .001). Telmisartan reduced baseline SABP of 179 mmHg by 19.2 (95% confidence interval [CI]: 15.92‐22.52) and 24.6 (95% CI: 21.11‐28.14) mmHg at Days 14 and 28. The placebo group baseline SABP of 177 mmHg was reduced by 9.0 (95% CI: 5.30‐12.80) and 11.4 (95% CI: 7.94‐14.95) mmHg, respectively. Of note, 52% of telmisartan‐treated cats had SABP <150 mmHg at Day 28. Mean SABP reduction by telmisartan in severe (≥180 mmHg) and moderate HT (160‐179 mmHg) was comparable and persistent over time. Conclusions and Clinical Importance Telmisartan solution (PO) was effective in reducing SABP in hypertensive cats with SABP ≥160 mmHg and ≤200 mmHg.
Exploration in Continuous Control Tasks via Continually Parameterized Skills

Applications of reinforcement learning to continuous control tasks often rely on a steady, informative reward signal. In videogames, however, tasks may be far easier to specify through a binary reward that indicates success or failure. In the absence of a steady, guiding reward, the agent may struggle to explore efficiently, especially if effective exploration requires strong coordination between actions. In this paper, we show empirically that this issue may be mitigated by exploring over an abstract action set, using hierarchically composed parameterized skills. We experiment in two tasks with sparse rewards in a continuous control environment based on the arcade game Asteroids. Compared to a flat learner that explores symmetrically over low-level actions, our agent explores a greater variety of useful actions, and its long-term performance on both tasks is superior.
Intensity-modulated radiotherapy combined with sequential cisplatin and fluorouracil chemotherapy for locoregionally advanced nasopharyngeal carcinoma

Abstract To investigate the efficacy and toxicity of intensity-modulated radiotherapy (IMRT) combined with induction-adjuvant cisplatin and fluorouracil (PF) in locoregionally advanced nasopharyngeal carcinoma (NPC). A total of 91 biopsy-proven NPC patients treated with IMRT were retrospectively analyzed. All patients received induction chemotherapy (IC) consisting of cisplatin 25 mg/m2 on day 1 to 3, and 5-Fu 2500 mg/m2 as an intravenous infusion over 120 hours every 3 weeks for 2 cycles. Adjuvant chemotherapy of the same regime was given 28 days after the end of IMRT. A total of 87 patients completed 2 cycles of IC. During adjuvant chemotherapy phase, 74.7% patients received at least 1 cycle. With a median follow-up time of 45 months (10–123 months), the 5-year local control, regional control, distant metastasis-free (DMF) and overall survival (OS) rates were 84.1%, 86.9%, 81.3%, and 74.4%, respectively. The 5-year local control rates for patients with Stage T1-2 and T3-4 was 94.6% and 76.5%, respectively (P = .045). The 5-year DMF rates for patients with N0-1 and N2-3 diseases were 90.6% and 73.3%, respectively (P = .072). During radiotherapy (RT), 24.2% patients suffered severe acute mucositis (grade 3–4). Severe late toxicities included cranial nerve palsy in 1 patient and grade 3 hearing impairment in 1 patient. IMRT combined with induction-adjuvant chemotherapy consisting of PF regimen is well tolerated and provides satisfactory local-regional control for locoregionally advanced NPC. Further treatment strategies to control distant metastasis are needed in the future.
What Predicts Stable Mental Health in the 18–29 Age Group Compared to Older Age Groups? Results from the Stockholm Public Health Cohort 2002–2014

Mental health has decreased in young people since the 1990s, and mental health promotion is an urgent matter. A first step is to identify which social determinants could be of importance for intervention. We used the Stockholm Public Health Cohort, a longitudinal population-based health survey, completed by 31,000 inhabitants in the Stockholm County. We focused on the 18–29 age group, n = 3373 (60% females, 40% males) and aimed at assessing which social determinants predict stable mental health, measured as scoring <3 points on the General Health Questionnaire 12 at all time points: 2002, 2007, 2010, and 2014. Forty-six percent of males and 36% of females reported stable mental health. Among the 17 predictors on sociodemographics, socioeconomics, social capital, health behavior, and victimization, six predicted stable mental health in the following order: occupation and especially employment, emotional support, male gender, being born in Sweden, absence of financial strain, and consumption of fruit and berries. In the 30–84 age group, 66% males and 55% females reported stable mental health. Nine determinants in the following rank predicted stable mental health: absence of financial strain, occupation and especially being self-employed, emotional support, male gender, physical activity, instrumental support, interpersonal trust, community trust, and absence of hazardous alcohol consumption. Interaction analysis showed significant difference between the younger and older group regarding physical activity and absence of financial strain with importance being higher for the older group. Our findings indicate that the determinants of health differ across the life-course with fewer predictors related to social capital and health behavior in the younger group compared to the older. We conclude that health-promoting interventions should be lifespan-sensitive.
Systematic review and meta-analysis of prognostic factors for idiopathic inflammatory myopathy-associated interstitial lung disease

Objective To clarify prognostic factors for idiopathic inflammatory myopathy (IIM)-associated interstitial lung disease (ILD). Design Systematic review and meta-analysis using the Grades of Recommendation, Assessment, Development and Evaluation system. Data sources Medline, EMBASE and Science Citation Index Expanded were searched through 9 August 2018. Eligibility criteria for selecting studies The review includes primary studies addressing all-cause mortality of IIM-associated ILD. Potential prognostic factors were any clinical information related to the outcome. Data extraction and synthesis Two reviewers extracted relevant data independently and assessed risk of bias using the Quality in Prognostic Studies tool. Meta-analysis was conducted using a random effects model and if inappropriate the results were reported qualitatively. Prognostic factors were determined based on statistically significant results derived from multivariate analysis. Results Of a total of 5892 articles returned, 32 were deemed eligible for analysis and cumulatively, these studies reported 28 potential prognostic factors for all-cause mortality. Each study was subject to certain methodological constraints. The four prognostic factors, which demonstrated statistically significant results on both univariate and multivariate analyses, were as follows: age (MD 5.90, 3.17–8.63/HR 1.06, 1.02–1.10 and 2.31, 1.06–5.06), acute/subacute interstitial pneumonia (A/SIP) (OR 4.85, 2.81–8.37/HR 4.23, 1.69–12.09 and 5.17, 1.94–13.49), percentage of predicted forced vital capacity (%FVC) (OR 0.96, 0.95–0.98/HR 0.96, 0.93–0.99) and anti-Jo-1 antibody (OR 0.35, 0.18–0.71/HR 0.004, 0.00003–0.54) (univariate/multivariate, 95% CI). Other prognostic factors included ground glass opacity/attenuation (GGO/GGA) and extent of radiological abnormality. The quality of the presented evidence was rated as either low or very low. Conclusions Older age, A/SIP, lower value of %FVC, GGO/GGA and extent of radiological abnormality were demonstrated to predict poor prognosis for IIM-associated ILD while a positive test for anti-Jo-1 antibody indicated better prognosis. However, given the weak evidence they should be interpreted with caution. Trial registration number CRD42016036999.
GT-Net: A Deep Learning Network for Gastric Tumor Diagnosis

Gastric cancer is one of the most common cancers, which causes the second largest number of deaths in the world. Traditional diagnosis approach requires pathologists to manually annotate the gastric tumor in gastric slice for cancer identification, which is laborious and time-consuming. In this paper, we proposed a deep learning based framework, namely GT-Net, for automatic segmentation of gastric tumor. The proposed GT-Net adopts different architectures for shallow and deep layers for better feature extraction. We evaluate the proposed framework on publicly available BOT gastric slice dataset. The experimental results show that our GT-Net performs better than state-of-the-art networks like FCN-8s, U-net, and achieved a new state-of-the-art F1 score of 90.88% for gastric tumor segmentation.
Voting with Random Neural Networks: a Democratic Ensemble Classifier

One of the main problems in machine learning is the investigation of the relationships between features in different datasets. In this case, using different classifiers can be more appropriate for different regions. Many efforts have been spent in looking for the best classifier and in fine tuning of the parameters. This requires knowledge of the domain and good expertise in fine tuning of the various classifiers. We propose a technique of voting with neural networks that does not require knowledge of the domain and avoids for a specific research of hyper-parameters values, because neural networks topology and the hyperparameters are generated at random from a uniform distribution. The output of each neural network can be considered as a ranking over the probabilities that each sample belongs to a class, so the output of each neural network is a preference over the classes. We aggregate these preferences via different voting rules and we provide an empirical evaluation of the approach.
Cross Entropy of Neural Language Models at Infinity—A New Bound of the Entropy Rate

Neural language models have drawn a lot of attention for their strong ability to predict natural language text. In this paper, we estimate the entropy rate of natural language with state-of-the-art neural language models. To obtain the estimate, we consider the cross entropy, a measure of the prediction accuracy of neural language models, under the theoretically ideal conditions that they are trained with an infinitely large dataset and receive an infinitely long context for prediction. We empirically verify that the effects of the two parameters, the training data size and context length, on the cross entropy consistently obey a power-law decay with a positive constant for two different state-of-the-art neural language models with different language datasets. Based on the verification, we obtained 1.12 bits per character for English by extrapolating the two parameters to infinity. This result suggests that the upper bound of the entropy rate of natural language is potentially smaller than the previously reported values.
SAE Network: A Deep Learning Method for Traffic Flow Prediction

Traffic flow forecasting is one of the most important work of the intelligent transport system (ITS). It has extensive and promising applications to improve the traffic conditions. However, the forecasting accuracy may not be high enough for traffic control considering high-dynamic change and various disturbance in the real world. In order to improve the forecasting accuracy, huge amount of historical traffic data are studied. In this paper, four months of aggregated traffic flow data via vehicle detector on a city ring way are obtained and selected for further analysis. An improved stacked autoencoder (SAE)model based on deep learning network is proposed to extract the features among traffic flow data. This predict model is trained in a greedy layer-wise method. The prediction results illustrate that this proposed model with higher accuracy is superior to other methods for traffic flow prediction.
Experiment Investigation of Radiation Losses of Bent Transmission Lines in Reverberation Chambers

In this paper, the stochastic electromagnetic field coupling to bent transmission lines above a conductive ground plane is investigated experimentally. A special focus lies on the radiation losses due to the bend. The measurements were performed in a reverberation chamber. Different bend angles of the transmission line were measured and the radiation losses were analyzed.
Effects of Molidustat in the Treatment of Anemia in CKD.

BACKGROUND AND OBJECTIVES The efficacy and safety of molidustat, a hypoxia-inducible factor-prolyl hydroxylase inhibitor, have been evaluated in three 16-week, phase 2b studies in patients with CKD and anemia who are not on dialysis (DaIly orAL treatment increasing endOGenoUs Erythropoietin [DIALOGUE] 1 and 2) and in those who are on dialysis (DIALOGUE 4). DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS DIALOGUE 1 was a placebo-controlled, fixed-dose trial (25, 50, and 75 mg once daily; 25 and 50 mg twice daily). DIALOGUE 2 and 4 were open-label, variable-dose trials, in which treatment was switched from darbepoetin (DIAGLOGUE 2) or epoetin (DIALOGUE 4) to molidustat or continued with the original agents. Starting molidustat ranged between 25-75 and 25-150 mg daily in DIAGLOGUE 2 and 4, respectively, and could be titrated to maintain hemoglobin levels within predefined target ranges. The primary end point was the change in hemoglobin level between baseline and the mean value from the last 4 weeks of the treatment period. RESULTS In DIAGLOGUE 1 (n=121), molidustat treatment was associated with estimated increases in mean hemoglobin levels of 1.4-2.0 g/dl. In DIAGLOGUE 2 (n=124), hemoglobin levels were maintained within the target range after switching to molidustat, with an estimated difference in mean change in hemoglobin levels between molidustat and darbepoetin treatments of up to 0.6 g/dl. In DIAGLOGUE 4 (n=199), hemoglobin levels were maintained within the target range after switching to molidustat 75 and 150 mg, with estimated differences in mean change between molidustat and epoetin treatment of -0.1 and 0.4 g/dl. Molidustat was generally well tolerated, and most adverse events were mild or moderate in severity. CONCLUSIONS The overall phase 2 efficacy and safety profile of molidustat in patients with CKD and anemia enables the progression of its development into phase 3.