Miracle-dz/UniFAR-FTUs huggingface dataset:
An Efficient Human Activity Recognition System Using WiFi Channel State Information

Insufficient recognition precision and high complexity are two main challenges of human activity recognition using WiFi channel state information (CSI), which has attracted more attention due to its low cost and easy realization. To address these challenges, we propose a novel framework based on Gramian angular fields (GAFs). This framework includes two transformation methods, Gramian angular sum field (GASF) and Gramian angular difference field (GADF), which effectively extract information from CSI and convert it into a CSI-GAF image. Subsequently, a convolutional neural network (CNN) is designed to analyze these images and obtain activity information. By incorporating a transformation module that preserves and expands the original CSI information, the proposed framework utilizes the powerful feature extraction capabilities of the CNN in image processing. Test results on public CSI datasets (Wiar, SAR, and Widar3.0) demonstrate that the recognition accuracy based on the GADF outperforms that of GASF, reaching 99.4% and 99.0%, respectively, when the CNN has only four convolutional layers. Moreover, the proposed framework exhibits low complexity, which outperforms three classical models (ResNet, VGG19, and ShufflenetV2) in terms of both parameters and required floating-point computations.
A Review on Human Stress Detection using Biosignal Based on Image Processing Technique

Stress is a problem in human life today. The pandemic caused by COVID-19 has also caused increased stress. Some people are aware of the stress they are experiencing and can control it, but some are unaware. Subsequently, it is vital to identify it early to anticipate worsening the condition. A noninvasive, easy, and convenient method is needed to predict daily life stress. One widely developed noninvasive stress detection method is the image processing technique. This technique uses images captured by cameras. Various image processing techniques are applied, i.e., extracting temperature, biosignal, and respiration parameters. This study investigated research on stress detection using biosignals based on image processing techniques. This research found that stress detection can be done using a webcam, a cheap and easy method to implement. Several limitations, such as accuracy and minimizing environmental influences, are still challenging to improve.
Phase II Window Study of Olaparib Alone or with Cisplatin or Durvalumab in Operable Head and Neck Cancer

Purpose: We conducted a phase II randomized noncomparative window of opportunity (WOO) trial to evaluate the inhibition of cellular proliferation and the modulation of immune microenvironment after treatment with olaparib alone or in combination with cisplatin or durvalumab in patients with operable head and neck squamous cell carcinoma (HNSCC). Experimental Design: Forty-one patients with HNSCC were randomized to cisplatin plus olaparib (arm A), olaparib alone (arm B), no treatment (arm C) or durvalumab plus olaparib (arm D). The primary endpoint was to evaluate the percentage of patients in each arm that achieved a reduction of at least 25% in Ki67. Secondary endpoints included objective response rate (ORR), safety, and pathologic complete response (pCR) rate. Paired baseline and resection tumor biopsies and blood samples were evaluated for prespecified biomarkers. Results: A decrease in Ki67 of at least 25% was observed in 44.8% of treated patients, as measured by quantitative immunofluorescence. The ORR among treated patients was 12.1%. pCR was observed in 2 patients. Two serious adverse events occurred in 2 patients. Programmed death ligand 1 (PD-L1) levels [combined positive score (CPS)] were significantly higher after treatment in arms A and D. Expression of CD163 and colony-stimulating factor 1 receptor (CSF1R) genes, markers of M2 macrophages, increased significantly posttreatment whereas the expression of CD80, a marker of M1 macrophages, decreased. Conclusion: Preoperative olaparib with cisplatin or alone or with durvalumab was safe in the preoperative setting and led to decrease in Ki67 of at least 25% in 44.8% of treated patients. Olaparib-based treatment modulates the tumor microenvironment leading to upregulation of PD-L1 and induction of protumor features of macrophages. Significance: HNSCC is characterized by defective DNA repair pathways and immunosuppressive tumor microenvironment. PARP inhibitors, which promote DNA damage and “reset” the inflammatory tumor microenvironment, can establish an effective antitumor response. This phase II WOO trial in HNSCC demonstrated the immunomodulatory effects of PARP inhibitor–induced DNA damage. In this chemo-naïve population, PARP inhibitor–based treatment, reduced tumor cell proliferation and modulated tumor microenvironment. After olaparib upregulation of PD-L1 and macrophages, suggests that combinatorial treatment might be beneficial. Synopsis: Our WOO study demonstrates that preoperative olaparib results in a reduction in Ki67, upregulation of PD-L1 CPS, and induction of protumor features of macrophages in HNSCC.
Two-bunch operation with ns temporal separation at the FERMI FEL facility

In the last decade, a continuous effort has been dedicated to extending the capabilities of existing free-electron lasers (FELs) operating in the x-ray and vacuum ultraviolet regimes. In this framework, the generation of two-color (or multi-color) temporally separated FEL pulses, has paved the way to new x-ray pump and probe experiments and several two-color two-pulse schemes have been implemented at the main facilities, but with a generally limited time-separation between the pulses, from 0 to few hundreds of fs. This limitation may be overcome by generating light with two independent electron bunches, temporally separated by integral multiples of the radio-frequency period. This solution was investigated at FERMI, measurements and characterization of this two-bunch mode of operation are presented, including trajectory control, impact of longitudinal and transverse wakefields, manipulation of the longitudinal phase space and finally a demonstration of suitability of the scheme to provide extreme ultraviolet light by using both bunches.
Sources of error in a Faraday magnetometer for magnetic microstructure analysis

In this work we examine a Faraday magnetometer built for microstructure analysis. We single out sources of error and quantitatively evaluate their effect on the measurement process. From this we derive a generalised estimation concerning temporal, spatial and amplitude resolution. We point out where the examined setup can be improved, but also where the limits of feasibility of a Faraday magnetometer as a means of measuring magnetic microstructures lie.
EFFECTIVENESS OF BALANCE TRAINING INTERVENTIONS IN IMPROVING BALANCE IN INDIVIDUALS WITH PARKINSON'S DISEASE: A SYSTEMATIC REVIEW

Objective: Parkinson's disease (PD) is a neurodegenerative disorder characterized by motor symptoms and non-physical symptoms, including pain, fatigue, and cognitive impairments. Balance impairments are common in individuals with PD and have a significant impact on their quality of life. Methods: This study involved a comprehensive systematic review of existing literature on balance training interventions for individuals with PD. The data collection was conducted at Pacific Medical College and Hospital, Udaipur. The study included a population of participants diagnosed with PD, and the study design involved randomization with a sample size of 60 subjects. Results: The results of the study indicate a significant difference in functional skills between Group A and Group B in all domains. This finding suggests that the two groups differ significantly in terms of their functional abilities across various areas. The observed differences may have important implications for understanding and addressing the unique needs and challenges faced by individuals in each group. Further research is warranted to explore the underlying factors contributing to these differences and to develop appropriate interventions or support strategies to enhance functional skills in both groups. Conclusion: The study highlights the effectiveness of balance training interventions in improving functional skills in individuals with PD. These findings align with previous research supporting the positive impact of interventions on cognitive abilities and functional outcomes in diverse populations. Tailored interventions targeting specific domains of functional skills can significantly enhance performance and improve quality of life for individuals with PD.
Effects of exercise based on ACSM recommendations on bone mineral density in individuals with osteoporosis: a systematic review and meta-analyses of randomized controlled trials

Purpose: To analyze the effects of different exercise dose on lumbar spine and femoral neck bone mineral density (BMD) in individuals with osteoporosis (OP). Design: A systematic search was conducted in four electronic databases, namely, PubMed, Embase, Web of Science, and Cochrane, with the topic of the impact of exercise on BMD in individuals with OP. Randomized controlled trials comparing exercise intervention with no intervention were identified, and changes in lumbar spine and femoral neck BMD were reported and evaluated using standardized mean difference (SMD) and 95% confidence interval (95% CI). The intervention measures in the studies were evaluated and categorized as high adherence with the exercise testing and prescription recommendations for individuals with OP developed by the American College of Sports Medicine (ACSM) or low/uncertainty adherence with ACSM recommendations. A random effects model was used to conduct meta-analyses and compare the results between subgroups. Results: A total of 32 studies involving 2005 participants were included in the analyses, with 14 studies categorized as high adherence with ACSM recommendations and 18 studies categorized as low or uncertain adherence. In the analyses of lumbar spine BMD, 27 studies with 1,539 participants were included. The combined SMD for the high adherence group was 0.31, while the combined SMD for the low or uncertain adherence group was 0.04. In the analyses of femoral neck BMD, 23 studies with 1,606 participants were included. The combined SMD for the high adherence group was 0.45, while the combined SMD for the low or uncertain adherence group was 0.28. Within resistance exercise, the subgroup with high ACSM adherence had a greater impact on lumbar spine BMD compared to the subgroup with low or uncertain ACSM adherence (SMD: 0.08 > −0.04). Similarly, for femoral neck BMD, resistance exercise with high ACSM adherence had a higher SMD compared to exercise with low or uncertain ACSM adherence (SMD: 0.49 > 0.13). Conclusion: The results suggest that exercise interventions with high adherence to ACSM recommendations are more effective in improving lumbar spine and femoral neck BMD in individuals with OP compared to interventions with low or uncertain adherence to ACSM recommendations. Systematic Review Registration: PROSPERO, identifier CRD42023427009
Pattern Recognition and Classification of Low-Intensity Emotions from Physiological Data

The recognition and evaluation of emotional states have important applications in the medical domain. Emotion recognition has been an active area of research in recent years, with a significant focus on data sources such as images or text, but also physiological signals like the electrocardiogram or electroencephalogram. However, traditional data collection and labelling methods often rely on exaggeratedly acted emotions or intense real emotions triggered by strong stimuli. These fail to mimic the conditions of most real world scenarios, where highly-intense emotional manifestations are not the most common. This work addresses these issues by evaluating the suitability of using physiological signals for emotion classification. We conducted a data collection protocol to acquire realistic emotional data in an isolated and undisturbed setup, with exposure to weak stimuli and standard activities, to capture low-intensity emotional manifestations. We present an initial exploratory analysis of physiological data, followed by the development of an emotion recognition training strategy using Machine Learning algorithms. Our approach achieved an optimal balanced accuracy of 47.97% and an area under the receiver operating characteristic curve of 72.09% for a multi-class classification problem with four emotion classes. Although the results may seem modest at a first glance, it is important to consider the inherent difficulty of distinguishing between subtle, low-intensity emotions, as well as the relevance of the problem to healthcare applications. Therefore, this work supports the development of more holistic, patient-centred healthcare solutions with emotion recognition.
Enhancing spatial resolution of two-wavelength digital holographic microscopy using speckle patterns generated from ring-slit apertures

Digital holographic microscopy (DHM) is actively investigated in the field of bio-imaging as a quantitative phase microscopy. In recent years, digital holographic technique for enhancing the spatial resolution using speckle patterns has been reported by several research groups, and we reported the enhancement of the spatial resolution in DHM using speckle illuminations generated from a ring-slit aperture. In this study, by applying the two-wavelength method to DHM using speckle illuminations, we realize the enhancement of spatial resolution and the extension of measurement range of shape measurement in DHM.
Development and psychometric properties of the transphobia scale among Indian adolescents

Background: Most of the studies employed in the concerning area use foreign scales or translated versions for measurement of transphobia. It isreally unfortunate a democratic country like India does not possesses anystandardized scale to measure the transphobia of adolescents. Purpose: Therefore, this study includes the development and validation of ascale for the assessment of transphobia in Indian adolescents. Methods: A total 516 students of CBSE school aged 14-16 years were sampled. The items for the preliminary transphobia scale were drawn after interviewing the adolescents, consultation with a reference group and review from existing standardized scales. A total 516 participants were assessed for psychometric properties of the scale. Criterion validity was evaluated by using the ATTMW (attitude toward transgender men and women) Scale. Results: Exploratory Factor Analysis (EFA) revealed six factors accounting for 65.30% of observed variance. The final 31-item scale contained six factors: Interpersonal Ease, Gender Prejudices, Gender Obstinacy, Human Values, Gender Stereotype and Gender Abuse. Transphobia scale was highly reliable in terms of internal consistency (Cronbach’s alpha 0.927). Criterion validity with the ATTMW was statistically significant. Conclusion: As the conclusion of the study, the Indian transphobia scale can be used as a reliable and valid tool for the measurement of transphobia for Indian adolescents.
Proteinase K/Retinoic Acid-Loaded Cationic Liposomes as Multifunctional Anti-Acne Therapy to Disorganize Biofilm and Regulate Keratinocyte Proliferation

Background Simultaneous anti-Cutibacterium acnes and anti-inflammatory actions are highly beneficial in treating acne vulgaris. In this study, we present novel anti-acne nanovesicles based on liposomes loaded with proteinase K (PK), retinoic acid (RA), and soyaethyl morpholinium ethosulfate (SME) to achieve an effective and safe treatment. Materials and Methods This study examined in vitro planktonic and biofilm C. acnes elimination, as well as the keratinocyte proliferation suppression by liposomes. The multifunctional liposomes for treating C. acnes in mice were also evaluated. Results We acquired multifunctional liposomes with a size of 71 nm and zeta potential of 31 mV. The antimicrobial activity of SME was enhanced after liposomal encapsulation according to the reduction of minimum bactericidal concentration (MBC) by 6-fold. The multifunctional liposomes exhibited a synergistically inhibitory effect on biofilm C. acnes colonization compared with the liposomes containing PK or those containing SME individually. The adhesive bacterial colony in the microplate was lessened by 62% after multifunctional liposome intervention. All liposomal formulations tested here demonstrated no cytotoxicity against the normal keratinocytes but inhibited C. acnes-stimulated cell hyperproliferation. The in vitro scratch assay indicated that the liposomal RA—but not free RA—restrained keratinocyte migration. The animal study showed that free RA combined with SME and multifunctional nanovesicles had a similar effect on diminishing C. acnes colonies in the skin. On the other hand, liposomes exhibited superior performance in recovering the impaired skin barrier function than the free control. We also found that RA-loaded nanovesicles had greater skin tolerability than free RA. Conclusion The cationic liposomes containing dual PK and RA represented a potential treatment to arrest bacterial infection and associated inflammation in acne.
Fucosyltransferase 9 promotes neuronal differentiation and functional recovery after spinal cord injury by suppressing the activation of Notch signaling

Individuals with spinal cord injury (SCI) suffer from permanent disabilities such as severe motor, sensory and autonomic dysfunction. Neural stem cell transplantation has proven to be a potential strategy to promote regeneration of the spinal cord, since NSCs can produce neurotrophic growth factors and differentiate into mature neurons to reconstruct the injured site. However, it is necessary to optimize the differentiation of NSCs before transplantation to achieve a better regenerative outcome. Inhibition of Notch signaling leads to a transition from NSCs to neurons, while the underlying mechanism remains inadequately understood. Our results demonstrate that overexpression of fucosyltransferase 9 (Fut9), which is upregulated by Wnt4, promotes neuronal differentiation by suppressing the activation of Notch signaling through disruption of furin-like enzyme activity during S1 cleavage. In an in vivo study, Fut9-modified NSCs efficiently differentiates into neurons to promote functional and histological recovery after SCI. Our research provides insight into the mechanisms of Notch signaling and a potential treatment strategy for SCI.
Contrasting Polarimetric Observations of Stratiform Riming and Nonriming Events

AbstractThis study investigates the how riming in stratiform precipitation impacts polarimetric signatures. Using a vertically pointing Doppler X-band radar, cases can be separated into one of three groups: unrimed to lightly rimed, riming with no bimodal spectra and fall speeds greater than 2.0 m s−1, and riming with bimodal velocity spectra. By averaging polarimetric variables over a 20° by 10-km box near the X-band radar, different signatures were documented for each of the three groups. These polarimetric signatures were then compared with a simplified T-matrix scattering model. Differential reflectivity ZDR was the one polarimetric variable to consistently vary across all three groups. Unrimed to lightly rimed cases had profiles of polarimetric signatures similar to numerous previous studies. Riming cases without detectable bimodal spectra had ZDR values on the order of 0.2 dB lower than unrimed to lightly rimed cases, while cases with bimodal spectra had ZDR values about 0.2–0.4 dB higher than unrim.
A Real-Time Control System of Upper-Limb Human Musculoskeletal Model With Environmental Integration

The intricate dynamics of the human musculoskeletal system require complex mathematical computations for accurate simulation, posing challenges in estimating muscle activity. Real-time processes and comprehensive analysis greatly influence the effectiveness of monitoring applications. The objective of our research was to enhance real-time muscle activity predictions by incorporating environmental data into human musculoskeletal simulations, focusing on the upper extremity. Our model, developed using MuJoCo software, consisted of 50 Hill-type muscles and integrated environmental context. Information on human posture was collected from single RGBD sensors positioned at 32 three-dimensional node locations. We used inverse kinematics computations to convert this data into joint angle parameters for our simulation model. The stretch reflex of each muscle was regulated to initiate movement in the target joints. Desired muscle stretch length was derived from the mechanical interaction between the bone structure and the muscle-tendon actuator connected to it. Our model also allowed for the application of artificial force to simulate external load conditions. To validate our model, we performed basic movements with the upper extremity and measured muscle activity using EMG sensors. Our results confirmed the model’s ability to accurately predict muscle activation and the force exerted by each muscle. Further experiments demonstrated its potential for seamless integration with dynamic environmental conditions, thereby enhancing its utility as a comprehensive human physical monitoring system.
MEASURING FUND PERFORMANCE USING MULTI-FACTOR MODELS: EVIDENCE FROM THE INDIAN MUTUAL FUNDS AND ULIP FUNDS.

Pardeep Kumar 1 , Dr. Harpreet Aneja 2 and Dr. Ashwani Kumar 3 . 1. Research Scholar, IKGPTU, Kapurthala, India. 2. Associate Professor, Gulzar Group of Institutes Khanna, India. 3. Research Guide, IKGPTU Kapurthala, India. Manuscript Info Abstract . Manuscript History
Adoption and impacts of conservation agriculture on smallholder farmers’ livelihoods in the case of Arba Minch Zuria district of Southern Ethiopia

Abstract The primary objective of this study was to evaluate the impact of conservation agriculture (CA) practice on farmers’ livelihood status and examine factors influencing the adoption of CA practice in Arba Minch Zuria district of Southern Ethiopia. The logistic regression model result revealed that gender, education level, credit access, access to extension service, household size, marital status, income, and cooperating group membership were crucial factors in influencing the likelihood of farmers adopting conservation agriculture practices. Moreover, the Propensity Score Matching (PSM) result indicated that the return from maize grain productivity and farmers’ annual income was comparatively higher in conservation agriculture practice than conventional agriculture practice. Thus, this study recommended promoting CA practice as a livelihood-enhancing technology in areas experiencing low yields and annual income.