Miracle-dz/UniFAR-FTUs huggingface dataset:
Poultry waste management practices in Bangladesh: Farmer’s perceptions, and food and environmental hazards

Objective: The poultry industry plays a key role in developing socio-economic and health sectors in Bangladesh. Poultry waste is a potential environmental threat as untreated poultry waste is used in vegetable gardens. The study aimed to investigate the current situation of small-scale poultry farms and their waste management practices in selected areas of Bangladesh and detect Escherichia coli and Salmonella in vegetables from farms using untreated poultry waste as fertilizer. Materials and Methods: A structured questionnaire-based survey was conducted in 86 small-scale poultry farms from different upazilas of Mymensingh and Khulna districts. 104 samples, including vegetables, poultry litter, water, and soil, were collected from vegetable gardens, ponds, fields, and wet markets in Mymensingh district to detect microbial contamination. Bacteria were identified based on their growth and colony morphology on selective media and motility tests. The presence of E. coli and Salmonella was confirmed by polymerase chain reaction (PCR) using a commercial PCR kit. Results: The survey revealed that mostly middle-aged males were involved in poultry farming. Most of the farmers had primary education and engaged in farming for about 5 years without training. In the study area, 37% of farmers collected droppings daily in the morning and used them as organic fertilizer. About 58% of farmers did not know the hygienic handlings of droppings and faced health problems. In PCR, either E. coli or Salmonella or both were confirmed in vegetables, litter, soil, and pond water. Conclusion: Appropriate poultry waste management practices can reduce the possible contamination of microbial agents in the human food chain.
Fifty-Five Years of Research on B, C and D in Escherichia coli

The basic properties of the Escherichia coli duplication process can be defined by two time periods: C, the time for a round of chromosome replication, and D, the time between the end of a round of replication and cell division. Given the durations of these periods, the pattern of chromosome replication during the cell cycle can be determined for cells growing with any doubling time. In the 55 years since these parameters were identified, there have been numerous investigations into their durations and into the elements that determine their initiations. In this review, I discuss the history of our involvement in these studies from the very beginning, some of what has been learned over the years by measuring the durations of C and D, and what might be learned with additional investigations.
IMPLEMENTASI BUSINESS INTELLIGENCE UNTUK MENENTUKAN TREND PENJUALAN BARANG (STUDI KASUS: PT. MENIKMATI DISTRIBUSI)

This study aims to analyze the implementation of Business intelligence to determine the trend in sales of goods in response to the needs of the company, make decisions, and choosing sales strategies. Business intelligence (BI) is one of the solutions dealing with company needs, especially analyzing and providing data access to help make or take better decisions. There are several stages could help the company to facilitate the decision making process, such as database design, data warehouse design, ETL (Extract, Transform, and Load) process, OLAP cube making and followed by report making. By seeing the report analyzes, the result of this study is the sale of goods in the Makassar area has the lowest contribution compared to other areas. The lowest sales by outlet can be seen from the O Voult Legian outlet which is ranked last with the fewest sales. Therefore, based on the results above the area or outlet that has the lowest contribution must be treated specifically. Conducting promotions and discounts is one of the objectives to increase the number of orders from customers with a greater range.
Multiwavelet prestack Kirchhoff migration

The problems of stretching and aliasing usually occur in prestack Kirchhoff migration. A multiwavelet-based approach is proposed to provide an alternative approach to resolve these problems. Two steps are involved in the multiwavelet-based algorithm: The first step is the decomposition of the seismic traces with a series of wavelets of different dominant frequencies. This step is based on the principle of basis pursuit and is enhanced for more accurate and sparse decomposition by adding an adaptive subdictionary that is associated with the minima and maxima of a seismic trace. The second step is wavelet migration based on the Kirchhoff formulation using a novel approach. The outer iteration is the wavelets of the input seismic traces, which ensures that an input wavelet is only used once in the entire migration process. This enables output of multiple migrated images of different wavelets of dominant frequency ranges, elimination of noisy images, and composition of images for specific interpretation and reservoir characterization purposes with very little extra computational cost. The stretching and aliasing problems are naturally resolved because interpolation on the seismic trace is not required in the migration. We tested the algorithm using a synthetic model with a dipping layer and a 2D real seismic section. We compared our results with results obtained by conventional Kirchhoff migration.
Cancer Risk in Patients Treated with the JAK Inhibitor Tofacitinib: Systematic Review and Meta-Analysis

Simple Summary Tofacitinib is a relatively novel therapy for immune-mediated inflammatory diseases, including rheumatoid arthritis, psoriatic arthritis, and ulcerative colitis. It is a small-molecule drug that exerts its effects by inhibiting Janus kinases. Recently, concerns have been raised about the drug’s safety in terms of cardiovascular side effects and cancer risk. This meta-analysis determined the risk of cancer in patients treated with tofacitinib for different clinical indications, compared to both a placebo and other therapies. We did not find any difference in the cancer risk between tofacitinib and either the placebo or biological drugs overall. In contrast, we found only a slightly higher risk of cancer in patients treated with tofacitinib compared with the patients treated with drugs that inhibit the tumor necrosis factor. Therefore, further studies are needed to better define the cancer risk of tofacitinib therapy. Abstract Tofacitinib is approved for several immune-mediated inflammatory diseases, but safety concerns have recently been raised. We searched PubMed (accessed on 27 February 2023) for original articles regarding tofacitinib’s cancer risk when used for rheumatoid arthritis, ulcerative colitis, Crohn’s disease, psoriatic arthritis, and ankylosing spondylitis. Of the 2047 initial records, 22 articles describing 26 controlled studies (including 22 randomized controlled trials) were selected. In the comparison between tofacitinib and any control treatment, the relative risk (RR) for any cancer was 1.06 (95% CI, 0.86–1.31; p = 0.95). In separate comparisons between tofacitinib and either a placebo or biological therapy, no difference was found in the overall cancer risk (vs. placebo, RR = 1.04; 95% CI, 0.44–2.48; p = 0.95; vs. biological drugs, RR = 1.06; 95% CI, 0.86–1.31; p = 0.58). When tofacitinib was compared to tumor necrosis factor (TNF) inhibitors, the overall cancer RR was 1.40 (95% CI, 1.06–2.08; p = 0.02). Similarly, significant results were obtained for all cancers, except for non-melanoma skin cancer (RR = 1.47; 95% CI, 1.05–2.06; p = 0.03), and for this skin cancer alone (RR = 1.30; 95% CI, 0.22–5.83; p = 0.88). In conclusion, no difference in the overall cancer risk was found between tofacitinib and either a placebo or biological drugs, while a slightly higher risk was found in patients treated with tofacitinib than anti-TNF agents. Further studies are needed to better define the cancer risk of tofacitinib therapy.
The bundle scheme for solving arbitrary eigenvalue optimizations

Optimization involving eigenvalues arises in a large spectrum of applications in various domains, such as physics, engineering, statistics and finance. In this paper, we consider the arbitrary eigenvalue minimization problems over an affine family of symmetric matrices, which is a special class of eigenvalue function--D.C. function \begin{document} $λ^_{l}$ \end{document} . An explicit proximal bundle approach for solving this class of nonsmooth, nonconvex (D.C.) optimization problem is developed. We prove the global convergence of our method, in the sense that every accumulation point of the sequence of iterates generated by the proposed algorithm is stationary. As an application, we use the proposed bundle method to solve some particular eigenvalue problems. Some encouraging preliminary numerical results indicate that our method can solve the test problems efficiently.
A study of kNN using ICU multivariate time series data

A time series is a sequence of data collected at successive time points. While most techniques for time series analysis have been focused on univariate time series data at fixed intervals, there are many applications where time series data are collected at irregular and uncertain time intervals across multiple input variables. The uncertainty in multivariate time series makes analysis difficult and challenging. In this research, we study kNN classification approach applied to ICU multivariate time series data for patient’s mortality prediction. We propose three time series representation strategies to handle irregular multivariate time series data. The experiments show the performance of these three methods in different settings. We also discuss the impact of imbalanced class distribution and the effect of k in kNN classification.
Some Multi-Dimensional Birth and Death Processes and Their Applications in Population Genetics

In this paper the change in number of the various genotypes in a population is formulated as a multi-dimensional birth and death process. Two classes of populations are considered, namely, bisexual diploid populations and asexual haploid populations. Various forms of the birth functions for the two classes of populations are deduced from biological considerations. Four multi-dimensional generalizations of classical one-dimensional cases are presented, and the generalized linear birth and death process is introduced. The generating function of the generalized linear birth and death process is found in some twoand three-dimensional cases, and the mean vector of the process for an arbitrary finite dimension and arbitrary parameters is also studied.
Image-guided cold atmosphere plasma (CAP) therapy for cutaneous wound

Bacterial infection is one of the major factors contributing to the compromised healing in chronic wounds. Sometimes bacteria biofilms formed on the wound are more resistant than adherent bacteria. Cold atmosphere plasma (CAP) has already shown its potential in contact-free disinfection, blood coagulation, and wound healing. In this study, we integrated a multimodal imaging system with a portable CAP device for image-guided treatment of infected wound in vivo and evaluated the antimicrobial effect on Pseudomonas aeruginosa sample in vitro.15 ICR mice were divided into three groups for therapeutic experiments:(1) control group with no infection nor treatment (2) infection group without treatment (3) infection group with treatment. For each mouse, a three millimeters punch biopsy was created on the dorsal skin. Infection was induced by Staphylococcus aureus inoculation one day post-wounding. The treated group was subjected to CAP for 2 min daily till day 13. For each group, five fixed wounds’ oxygenation and blood perfusion were evaluated daily till day 13 by a multimodal imaging system that integrates a multispectral imaging module and a laser speckle imaging module. In the research of relationship between therapeutic depth and sterilization effect on P.aeruginosa in agarose, we found that the CAP-generated reactive species reached the depth of 26. 7μm at 30s and 41. 6μm at 60s for anti-bacterial effects. Image-guided CAP therapy can be potentially used to control infection and facilitate the healing process of infected wounds.
A model-free 6-DOF grasp detection method based on point clouds of local sphere area

ABSTRACT Grasping object is one of the basic tasks of robots in many scenarios. The main challenge is how to generate grasping poses for unknown objects in cluttered scenes. This paper proposes a model-free 6-DOF grasp detection framework based on single-view local point clouds. The whole process includes three stages: Candidate Generation Network(CGN), Reliable Adjustment Module(RAM), and Quality Assessment Network(QAN). CGN predicts the graspability and the initial grasp pose of the sampled points by the features extracted from the local sphere region based on the improved Pointnet. In order to better learn local area point clouds, we propose a progressive local region data learning mechanism, which can extract features from small to large scales efficiently. Candidate grasps are then consisting of graspable points and their grasping poses. RAM adjusts the position and width of the generated candidate grasps by using reliable heuristic rules. QAN uses a simpled-pointnet to evaluate the quality of the grasp candidates and filters out grasps with high confidence to execute. The proposed method not only achieves state-of-the-art results on GraspNet-1Billion but also shows high grasping success rates in real cluttered scenes. GRAPHICAL ABSTRACT
Pet animals as reservoirs for spreading methicillin-resistant Staphylococcus aureus to human health

Methicillin-resistant Staphylococcus aureus (MRSA) is a strain of pathogenic bacteria that is a major problem in the world’s health. Due to their frequent interaction with humans, pets are one of the main risk factors for the spread of MRSA. The possibility for zoonotic transmission exists since frequently kept dogs and cats are prone to contract MRSA and act as reservoirs for spreading MRSA. The mouth, nose, and perineum are the primary locations of MRSA colonization, according to the findings of MRSA identification tests conducted on pets. The types of MRSA clones identified in cats and dogs correlated with MRSA clones infecting humans living in the same geographic area. A significant risk factor for the colonization or transmission of MRSA is human-pet contact. An essential step in preventing the spread of MRSA from humans to animals and from animals to humans is to keep hands, clothing, and floor surfaces clean.
An Easily Initialized Visual Tracking Algorithm Based on Similar Structure for Convolutional Neural Network

On the issues about the robustness in visual object tracking, based on Principal Component Analysis(PCA) and Convolutional Neural Network(CNN), a novel visual tracking algorithm with deep feature, which is acquired from a easily initialized CNN structure, is proposed. First, the original image is processed by affine transformation. Next, layered PCA learning is used to process the normalized size image, the eigenvectors learned by PCA are used to be the filters of a CNN structure to realize initialization. Then, the deep expression of the object is extracted by this CNN structure. Finally, combining particle filter algorithm, a simple logistic regression classifier is used to realize target tracking. The result shows that the deep feature acquired from the easily initialized CNN structure has a better expressivity, it can distinguish the object and background effectively. The proposed algorithm has a better inflexibility to illumination, occlusion, rotation and camera shake, and it exhibits a good robustness and accuracy in many video sequences.
Micro-Transfer-Printed Membrane Distributed Reflector Lasers on Si Waveguide Modulated With 50-Gbit/s NRZ Signal

In this work, we fabricate directly modulated membrane distributed reflector (DR) lasers on a Si waveguide by utilizing micro-transfer printing method. Micro-transfer printing enables low-loss coupling between the lasers and the silicon photonics circuit, and since it is a back-end process, we can test the lasers prior to integration. A membrane laser is as thick as the Si waveguides, which makes optical coupling between the two quite easy. In addition, membrane lasers with a lateral p-i-n diode structure have low capacitance and a large optical confinement factor, which means they can achieve a low threshold current and high-speed modulation operation with low energy consumption. The fabricated membrane DR laser integrated with a 220-nm-thick Si waveguide exhibits a low threshold current of 1.2 mA and single-mode operation at 1535 nm with a side-mode suppression ratio (SMSR) of about 40 dB at the bias current of 14 mA. It also achieves the E-O bandwidth of over 25 GHz and 50-Gbit/s non-return-to-zero (NRZ) signal modulation with an extinction ratio of 2.5 dB.
Highly Sensitive Dual-Core Microstructured Fiber Sensor Operating Near the Dispersion Turning Point

In this article, a highly sensitive dual-core microstructured fiber (DC-MSF) sensor is proposed. Because of the adjustable dispersion characteristic of the DC-MSF, the group refractive index (RI) difference between the ${y}$ -polarization odd and even supermodes could achieve a zero value at the dispersion turning point (DTP), which makes the DC-MSF sensor have a high sensitivity. The simulation results show that the sensitivity can be up to 52 875 nm/RIU around the RI of 1.4, the operating bandwidth of sensitivity over 104 nm/RIU is 625 nm, and the operating bandwidth of sensitivity over 105 nm/RIU is 100 nm. Moreover, the DC-MSF can also be used as a temperature sensor by coating the polydimethylsiloxane (PDMS) on the surface, and the sensitivity can be up to 23.12 nm/°C around 22 °C. The detectable RI and temperature ranges of the proposed DC-MSF sensor are 1.375–1.425 and −15 °C–95 °C, respectively.
Performance Evaluation of Probabilistic Interest Forwarding in NDN over LLNs

This study investigates the merits of adopting probabilistic interest forwarding in Named Data Networks (NDN) deployed over IEEE 802.15. 4 communication technologies, which are also known as Low-power & Lossy Networks (LLNs), considering their limited capabilities including computation, energy, and communication. To this end, we evaluate the performance of probabilistic forwarding and compared it against that of Deferred Blind Flooding (DBF) which is one of the most widely used strategies for interest forwarding in NDN. Our performance results reveal that probabilistic forwarding exhibits superior performance over DBF with respect to important performance measures such as number of sent packets and latency while achieving high interest satisfaction rates.
Electrocardiographic Predictors of Atrial Fibrillation

Background: Atrial fibrillation (AF) is the most common pathological arrhythmia, and its complications lead to significant morbidity and mortality. However, patients with AF can often go undetected, especially if they are asymptomatic or have a low burden of paroxysms. Identification of those at high risk of AF development may help refine screening and management strategies. Methods: PubMed and Embase databases were systematically searched for studies looking at electrocardiographic predictors of AF from inception to August 2021. Results: A total of 115 studies were reported which examined a combination of atrial and ventricular parameters that could be electrocardiographic predictors of AF. Atrial predictors include conduction parameters, such as the PR interval, p-wave index and dispersion, and partial interatrial or advanced interatrial block, or morphological parameters, such as p-wave axis, amplitude and terminal force. Ventricular predictors include abnormalities in QRS amplitude, morphology or duration, QT interval duration, r-wave progression and ST segment, i.e., t-wave abnormalities. Conclusions: There has been significant interest in electrocardiographic prediction of AF, especially in populations at high risk of atrial AF, such as those with an embolic stroke of undetermined source. This review highlights the breadth of possible predictive parameters, and possible pathological bases for the predictive role of each parameter are proposed.
Automated segmentation and measurement of the levator hiatus in 3D transperineal ultrasound

Three-dimensional (3D) transperineal ultrasound (TPUS) is a valuable imaging tool for evaluating patients with a variety of pelvic floor disorders, including pelvic organ prolapse (POP). Patients with POP have abnormal descent of one or more pelvic organs (i.e., bladder, uterus, vagina) through the levator hiatus, which is often experienced by the patient as a persistent bothersome bulge protruding from the vaginal opening. The enlargement of the hiatal opening measured in the plane of minimal hiatal dimensions (PMHD), has been used as an indication for POP severity. Manually measuring the size of the levator hiatus in 3D TPUS images can be challenging and requires expertise and training and is timeconsuming. Hence a fully automated method for estimating the dimensions of hiatal opening is highly desirable. To this end, we developed a fully automated method to segment the levator hiatus from the PMHD based on the nnU-Net model framework. We trained, validated, and tested on a total of 252 3D US images from 138 patients that may have POP as determined by the pelvic organ prolapse quantification (POP-Q) system. As a benchmark comparison, we compared the nnU-Net to a vanilla U-Net whose hyperparameters were manually tuned. Model performance was determined using Dice similarity coefficient (DSC) and levator hiatus width, length, and area by comparing the model segmentations to manual segmentations. The nnU-Net achieved a DSC of 93.1%±3.3%, absolute width difference of 2.3mm±1.7mm, absolute length difference of 2.6mm±2.5mm and absolute area difference of 1.8cm2±1.3cm2.
Progesterone Resistance in Endometriosis: Current Evidence and Putative Mechanisms

Endometriosis is an estrogen-dependent disease characterized by the growth of endometrial-like tissue outside the uterus. Progestins are currently the most commonly used treatment for endometriosis because of their excellent therapeutic effects and limited side effects. However, progestins have been unsuccessful in some symptomatic patients. The inability of the endometrium to respond properly to progesterone is known as progesterone resistance. An increasing body of evidence suggests the loss of progesterone signaling and the existence of progesterone resistance in endometriosis. The mechanisms of progesterone resistance have received considerable scholarly attention in recent years. Abnormal PGR signaling, chronic inflammation, aberrant gene expression, epigenetic alterations, and environmental toxins are considered potential molecular causes of progesterone resistance in endometriosis. The general objective of this review was to summarize the evidence and mechanisms of progesterone resistance. A deeper understanding of how these mechanisms contribute to progesterone resistance may help develop a novel therapeutic regimen for women with endometriosis by reversing progesterone resistance.